Released this past November, the list is based on data collected from the Web of Science and highlights some of the world’s most influential scientific minds by naming the researchers whose publications over the previous decade have included a high number of Highly Cited Papers placing them among the top 1% most-cited.
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We wish to congratulate all of the researchers named and especially our authors on this amazing accomplishment! We are happy and proud to share in their success!
IntechOpen is proud to announce that 191 of our authors have made the Clarivate™ Highly Cited Researchers List for 2020, ranking them among the top 1% most-cited.
\n\n
Throughout the years, the list has named a total of 261 IntechOpen authors as Highly Cited. Of those researchers, 69 have been featured on the list multiple times.
\n\n\n\n
Released this past November, the list is based on data collected from the Web of Science and highlights some of the world’s most influential scientific minds by naming the researchers whose publications over the previous decade have included a high number of Highly Cited Papers placing them among the top 1% most-cited.
\n\n
We wish to congratulate all of the researchers named and especially our authors on this amazing accomplishment! We are happy and proud to share in their success!
Note: Edited in March 2021
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This book deals with the basic principles of hypoxia and oxygenation in terms of functional airway anatomy and intubation requirements as well as difficult airway algorithms.",isbn:"978-1-78923-489-3",printIsbn:"978-1-78923-488-6",pdfIsbn:"978-1-83881-502-8",doi:"10.5772/intechopen.70975",price:119,priceEur:129,priceUsd:155,slug:"tracheal-intubation",numberOfPages:136,isOpenForSubmission:!1,isInWos:null,isInBkci:!1,hash:"974314e3b82efe09e1ee95861c21554c",bookSignature:"Riza Hakan Erbay",publishedDate:"July 25th 2018",coverURL:"https://cdn.intechopen.com/books/images_new/6495.jpg",numberOfDownloads:16009,numberOfWosCitations:8,numberOfCrossrefCitations:13,numberOfCrossrefCitationsByBook:0,numberOfDimensionsCitations:20,numberOfDimensionsCitationsByBook:0,hasAltmetrics:1,numberOfTotalCitations:41,isAvailableForWebshopOrdering:!0,dateEndFirstStepPublish:"November 23rd 2017",dateEndSecondStepPublish:"December 14th 2017",dateEndThirdStepPublish:"February 12th 2018",dateEndFourthStepPublish:"May 3rd 2018",dateEndFifthStepPublish:"July 2nd 2018",currentStepOfPublishingProcess:5,indexedIn:"1,2,3,4,5,6",editedByType:"Edited by",kuFlag:!1,featuredMarkup:null,editors:[{id:"169248",title:"Dr.",name:"Rıza Hakan",middleName:null,surname:"Erbay",slug:"riza-hakan-erbay",fullName:"Rıza Hakan Erbay",profilePictureURL:"https://mts.intechopen.com/storage/users/169248/images/5141_n.png",biography:"Dr. Riza Hakan Erbay has become an anesthesiologist at Pamukkale University in 1996. He has obtained his titles of assistant professor in 1997, associate professor in 2005, and professor in 2011. He has mainly worked in the field of orthopedic anesthesia, regional anesthesia and intensive care medicine. He worked as Education Coordinator in the Faculty of Medicine during 2007-2009. He served as Vice-President of Surgical Sciences Department of Faculty of Medicine during 2009-2012. He has obtained the title of Intensivist in 2013. He worked as a Head of the Anesthesiology Clinic in Izmir Tepecik Training and Research Hospital during 2013-2014. He is currently the Chairman of Department of Anesthesiology and Reanimation at the Faculty of Medicine of Pamukkale University.",institutionString:null,position:null,outsideEditionCount:0,totalCites:0,totalAuthoredChapters:"1",totalChapterViews:"0",totalEditedBooks:"3",institution:{name:"Pamukkale University",institutionURL:null,country:{name:"Turkey"}}}],equalEditorOne:null,equalEditorTwo:null,equalEditorThree:null,coeditorOne:null,coeditorTwo:null,coeditorThree:null,coeditorFour:null,coeditorFive:null,topics:[{id:"1139",title:"Anesthesiology",slug:"surgery-anesthesiology"}],chapters:[{id:"61712",title:"Functional Anatomy and Physiology of Airway",doi:"10.5772/intechopen.77037",slug:"functional-anatomy-and-physiology-of-airway",totalDownloads:3790,totalCrossrefCites:1,totalDimensionsCites:5,hasAltmetrics:0,abstract:"In this chapter, we scope the importance of functional anatomy and physiology of the upper airway. The upper airway has an important role in transporting air to the lungs. Both the anatomical structure of the airways and the functional properties of the mucosa, cartilages, and neural and lymphatic tissues influence the characteristics of the air that is inhaled. The airway changes in size, shape, and position throughout its development from the neonate to the adults. Knowledge of the functional anatomy of the airway in these forms the basis of understanding the pathological conditions that may occur. The upper airway extends from the mouth to the trachea. It includes the mouth, the nose, the palate, the uvula, the pharynx, and the larynx. This section also describes the functional physiology of this airway. Managing the airway of a patient with craniofacial disorders poses many challenges to the anesthesiologist. Anatomical abnormalities may affect only intubation, only airway management, or both. This section also focuses on the abnormal airways in obesity, pregnancy, children and neonate, and patients with abnormal facial defects.",signatures:"Aslı Mete and İlknur Hatice Akbudak",downloadPdfUrl:"/chapter/pdf-download/61712",previewPdfUrl:"/chapter/pdf-preview/61712",authors:[{id:"237495",title:"Dr.",name:"Asli",surname:"Mete",slug:"asli-mete",fullName:"Asli Mete"},{id:"237882",title:"Dr.",name:"Ilknur",surname:"Akbudak",slug:"ilknur-akbudak",fullName:"Ilknur Akbudak"}],corrections:null},{id:"61680",title:"Pathophysiology of Apnea, Hypoxia, and Preoxygenation",doi:"10.5772/intechopen.76851",slug:"pathophysiology-of-apnea-hypoxia-and-preoxygenation",totalDownloads:1797,totalCrossrefCites:2,totalDimensionsCites:2,hasAltmetrics:0,abstract:"Because intubation becomes a long procedure as potential, arterial oxygen (O2) desatu-ration should be taken into account during the intubation. Since oxygen reserves are not always sufficient to meet the duration of intubation, preoxygenation should be routine before anesthetic induction and tracheal intubation. Surveys show that maximal preoxygenation increases oxygen reserves in the body and significantly delays arterial hemoglobin desaturation and hypoxia. In cases of respiratory insufficiency oxygenation can be improved by positive end expiratory pressure (PEEP) or pressure support. Effective technique and FeO2 monitoring can increase the effectiveness of preoxygenation and thus increase the safety margin. Preoxygenation failures have to be identified and alternative oxygenation methods must be readily available in order to be applied quickly and easily. Although genetic and environmental factors play a role in diseases such as heart attack, stroke and cancer, which have become the cause of the worst death in the twenty-first century, the underlying problem in the development of these pathological conditions is hypoxia. Better understanding of hypoxic areas in ischemic tissues or growing tumors as well as increased knowledge of hypoxia cellular and molecular responses will allow possible applications in the treatment of major diseases associated with tissue hypoxia.",signatures:"Ilknur Hatice Akbudak and Asli Mete",downloadPdfUrl:"/chapter/pdf-download/61680",previewPdfUrl:"/chapter/pdf-preview/61680",authors:[{id:"237495",title:"Dr.",name:"Asli",surname:"Mete",slug:"asli-mete",fullName:"Asli Mete"},{id:"237882",title:"Dr.",name:"Ilknur",surname:"Akbudak",slug:"ilknur-akbudak",fullName:"Ilknur Akbudak"}],corrections:null},{id:"60582",title:"Indications for Endotracheal Intubation",doi:"10.5772/intechopen.76172",slug:"indications-for-endotracheal-intubation",totalDownloads:3724,totalCrossrefCites:1,totalDimensionsCites:0,hasAltmetrics:0,abstract:"Endotracheal intubation may be required when respiratory distress or airway integrity cannot be achieved or maintained for any reason. It should be considered that intubation may be required when evaluating the patient, and that in the long term, airway protection will be needed or that the problem cannot be solved by noninvasive ventilation via airway aids and devices. Identifying the problem causing the patient’s respiratory failure helps in making the decision to intubate. In fact, the clinician must be fast and self-confident when deciding on intubation. It is difficult to decide in some complex situations. It is very important to evaluate the patient, according to clinical status, age, and comorbidity, and to determine urgent intubation need. In non-diagnostic cases, further research is needed to investigate the causes of the condition such as hypoxia/hypercapnia resulting in patient respiratory distress. Different voice tone, swallowing difficulties, coughing attacks, stridor, dyspnea can be a sign of upper airway obstruction. Arterial blood gas analysis will facilitate our decision to make intubation. Non-invasive pulse oximetry and continuous capnography values may also be a guide, but the most important thing is that delayed intubation decision may bring life-threatening situations.",signatures:"Yeliz Şahiner",downloadPdfUrl:"/chapter/pdf-download/60582",previewPdfUrl:"/chapter/pdf-preview/60582",authors:[{id:"236458",title:"Dr.",name:"Yeliz",surname:"Şahiner",slug:"yeliz-sahiner",fullName:"Yeliz Şahiner"}],corrections:null},{id:"60584",title:"The Importance of Proper Positioning for Airway Management for Obese Patients",doi:"10.5772/intechopen.75514",slug:"the-importance-of-proper-positioning-for-airway-management-for-obese-patients",totalDownloads:1996,totalCrossrefCites:2,totalDimensionsCites:2,hasAltmetrics:1,abstract:"In the practice of anesthesia patient care, airway management is the first and most important consideration when caring for all patients. In particular, when caring for obese patients, airway positioning requires additional special attention. The head-elevated laryngoscopy position (HELP) has been presented as the best starting point to improve patient safety, lower risk, and facilitate a successful first attempt at intubation. HELP has also been described as the ramped position.",signatures:"Craig A. Troop",downloadPdfUrl:"/chapter/pdf-download/60584",previewPdfUrl:"/chapter/pdf-preview/60584",authors:[{id:"236928",title:"Dr.",name:"Craig",surname:"Troop",slug:"craig-troop",fullName:"Craig Troop"}],corrections:null},{id:"59759",title:"Long-Term Complications of Tracheal Intubation",doi:"10.5772/intechopen.74160",slug:"long-term-complications-of-tracheal-intubation",totalDownloads:3145,totalCrossrefCites:7,totalDimensionsCites:11,hasAltmetrics:1,abstract:"Endotracheal intubation is an intervention frequently performed in the hospital setting in order to protect the central airway and provide mechanical support of ventilation. Many health care providers are expected to be able to intubate the patients for different indications. As the case in any medical intervention, endotracheal intubation can cause complications. These complications are categorized as early or late according to the time of onset of the presenting symptoms. This chapter will discuss the long term complications of endotracheal intubation that might be encountered by the treating physicians. The chapter will stress on the predisposing factors for these complications and the available methods to avoid and treat them.",signatures:"Abdelfattah A. Touman and Grigoris K. 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Finally, the role of the Otolaryngologist-Head and Neck Surgeon will be highlighted in the difficult airway team which should be multidisciplinary when handling airway concerns in a hospital. Overall, the goals of this chapter are to educate the reader on how to critically analyze and decide on the means to adopt a difficult airway algorithm in their own institution(s).",signatures:"Vaninder K. 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1. Introduction
Photography has a vast history as it is used to preserve our lives’ most important memories. As such, it tries to conserve a scene as realistically as possible. During the years, it evolved from the camera obscura [1, 2] where scenes were captured only for a brief moment, to black and white photography, requiring to stay still in front of the camera for long hours, to nowadays imaging devices, where the picture is captured instantaneously, digitalized, and the colors are close to what our eyes perceive [3].
Though it preserves the content of the scene, the immersion is lost, as well as the depth information, since the camera projects the scene from 3D to 2D.
To increase the immersion, the next step is to recreate the parallax of the scene, giving the opportunity to the viewer to move freely and see different perspectives, exactly as if the subject was miniaturized in front of our eyes, or the environment virtually rendered around us. Despite this desire, no device capable of acquiring the scene in its entirety directly in 3D has been designed so far.
Creating the parallax effect assumes capturing the scene from all the possible viewpoints and selecting the viewpoint to display on demand for the user’s viewing position. This is physically impossible; instead, we may synthesize any viewpoint from only a couple of captured viewpoints generating all missing information following some basic assumptions [4, 5].
There exist many approaches to generate novel viewpoints from input views. Early methods were based on 3D reconstruction [6, 7] to render the obtained 3D model. More recently, neural radiance fields (NeRF) [8] used machine learning methods to recreate a volumetric representation of the scene. Other methods avoid the explicit 3D information reconstruction, such as depth image-based rendering (DIBR) [9] that will be described in this chapter, or multiplane images [10, 11]. Finally, novel viewpoints can be synthesized by an intelligent interpolation using physical invariants (the epipolar plane image), rather than interpolating directly the image’s colors. Representatives of this last category are the shearlet transform [12] and techniques using deep learning [13].
This chapter provides comprehensive elements to bring photographs of a natural scene to the third dimension, for example, making the captured scene immersive, through holography or virtual reality (VR). The presented 3D rendering technique differs from traditional computer graphics by its input—instead of modeling 3D objects with their geometry and materials that interact with light sources, we use photographs that are warped to follow the viewer gaze direction using the reference view synthesis (RVS) [14, 15, 16] software that follows the view synthesis process of Figure 1.
Figure 1.
DIBR brings photographs to 3D by using depth information to create new viewpoints. It preserves photorealism and allows the user to experience motion parallax.
RVS has been developed during the exploration and standardization activities of MPEG-I – where “I” refers to Immersive – focusing on developing new compression and file formats for immersive video.
The chapter is structured as follows—the first part explains the principles of depth image-based rendering, gives an overview of the possible artifacts that can be encountered when creating a DIBR implementation, and finally, implementation details of RVS are described. The second part provides practical advice for using RVS on some example datasets.
2. Principles of depth image-based rendering
To recreate the parallax effect, we use the depth image-based rendering [9] method. It warps or distorts the input color image as a function of its associated depth map, which itself stores, for every pixel, the distance between the camera and the projected point along the camera optical axis. This method is based on the observation that a stereoscopic pair of images, for example, taken with a few centimeters shift between each other, carry the depth information of the photographed subject. As shown in Figure 2, the relative shift d, aka. the disparity, of foreground objects is larger than for background objects.
Figure 2.
Disparity d=d2−d1 between two pixels representing the same projected point.
2.1 Projection equation and disparity
Let us consider two pinhole cameras facing an object at distance D (see Figure 2). The projection of this object on each image will have a disparity d. Using the similar triangles ratios of fD and d1+d2B, we obtain:
d=B×fDE1
where B is the baseline, i.e., the distance between the two camera centers, and f their focal length.
This implies that, given two images and their depth maps, we can create a virtual view in the middle, between the inputs, by shifting the pixels over half their disparity.
Eq. 1 can be generalized to any camera settings using the pose (translation and rotation – extrinsic parameters, Eq. 2) and internal camera parameters (focal length fx and fy expressed in pixels in the x and y directions, and principal point ppxppy – intrinsic parameters, Eq. (3).
We call an input image and its camera parameters an input viewpoint. We aim to recreate a new virtual view with given new parameters, called target viewpoint. For this, we deproject (i.e., from 2D to 3D) the pixels of the input image to 3D, and reproject (i.e., from 3D to 2D) them to the target image using the projection equation.
Let P=Rt be the inverse (i.e., world to camera) 3×4 pose matrix of a camera with R the rotation matrix and t the translation:
P=Rt=r11r12r13txr21r22r23tyr31r32r33tz,E2
and K its 3×3 intrinsic matrix:
K=fx0ppx0fyppy001.E3
In homogeneous coordinates, a point X=xyz1t at depth D from the input camera pin=uv1t is projected to a pixel pin=uv1t following the projection Equation [6]:
Dpin=KinPinXE4
Hence, given the input image and the depth value of the pixel, we can deproject X:
X=DRin−Rin−1tinTKin−1pinE5
Eventually, this allows to reproject X in the new camera, using Eq. 4 with Pout and Kout:
pout∝DKoutPoutRin−Rin−1tinTKin−1pinE6
To obtain the pixel value, we divide the obtained vector by the third coordinate (i.e., the depth of the point in the new camera).
Applying this operation to every pixel of the input image creates a novel view.
The core principle of DIBR is to apply this deprojection and reprojection to all the pixels of the input images, using a depth map (i.e., a single-channel image encoding the depth value of each pixel). RVS uses this basic principle, but of course, there are many pitfalls one should handle correctly. This is further explained in the following sections.
2.2 Frequent artifacts
We now know the basic principles of DIBR. Unfortunately, simply shifting the pixels of an input image in the function of their depth does not create a photo-realistic result.
The first problem is occlusion handling. When an object is visible in the input image but hidden by an object lying more in the foreground in the target, it is occluded and its pixels should not appear in the rendered image. This can be solved by choosing, among all the pixels from various objects ending up in the same pixel on the screen, the pixel with the minimal depth. A more critical problem is the one of disocclusions, for example, when an object should be visible in the target image but does not appear in the input image because it is hidden (Figure 3a). In that case, a hole is created in the rendered image. One solution is to add more input images in the hope to obtain this missing information [15, 17]. Another approach is to inpaint the empty pixels [18, 19]. In RVS, it is possible to choose any number of viewpoints and a basic inpainting fills the remaining disocclusions.
Figure 3.
(a) Disocclusion artifact (classroom dataset), (b) crack artifacts (Toystable dataset), (c) Artifacts due to inconsistency in color among the input images. (dataset fencing, courtesy of Poznan University of Technology), (d) ghosting artifacts (dataset Toystable).
Cracks and dilation are other frequent DIBR artifacts. We can observe them in Figure 3b. They are created as the user moves forward (step-in), increases the resolution (zoom), or observes slanted objects. Those cracks correspond to pixels in the target that do not have a preimage in the input view (i.e., no input pixel is mapped to them). However, as their neighboring pixels have a preimage, their color can be interpolated. In other words, the input pixels should be mapped to more than one pixel to compensate for this effect. This can be done using superpixels [20], adapting the pixels size to the camera movement [21], or linking neighboring pixels for rasterization [15, 16] (chosen solution in RVS: adjacent pixels are grouped into triangles that are colorized).
Even if increasing the number of input images can reduce the number of disocclusions, it brings new challenges, as those views need to be consistent in color, in estimated geometry, and in estimated pose. Notably, the depth estimation and the blending of multiple views together rely on consistent colors between the images. As not all camera sensors are equal, small differences in color rapidly generate incoherent depth estimations or nonhomogeneous color patches during view blending (Figure 3c). Color correction is usually needed prior to the view synthesis [22, 23] or during the blending step [24, 25].
Moreover, as DIBR relies on the depth information, errors in the depth estimation, a misalignment between the color image and the depth map, or errors in the camera pose estimation lead to ghosting artifacts. When several views are blended together, these artifacts make the objects or their borders appear doubled (Figure 3d). A depth map refinement [26, 27] is one way to solve this problem. Another is to choose weighted blending coefficients based on the reliability of each input image [11, 16] (chosen solution in RVS).
Finally, DIBR is structurally limited to the rendering of diffuse objects. Indeed shifting the pixels in the function of their depth assumes that they do not present view-dependent aspects, such as transparency or specularity. When such objects, so-called non-Lambertian, are present in the scene, the linear hypothesis in pixel displacement in the function of the camera displacement is not valid anymore. Adapting the DIBR principles to non-Lambertian objects is nevertheless possible by exploiting additional information, such as structure, normal, and indexes of refraction [28], or a more accurate approximation of the pixel displacement [29–31] (chosen solution in RVS).
2.3 RVS in practice
The DIBR software RVS is designed to render novel viewpoints from any number of input images and depth maps and their camera parameters, without suffering from the above limitations. In order to create a novel view, the input images are warped sequentially. The obtained result is then blended into an image accumulating the outputs of each reprojected input image. This pipeline is shown in Figure 4. The warping and blending operations are performed alternatively for each input image using OpenGL [32] or on the CPU [15].
Figure 4.
Overview of the processing pipeline. (1) view selection (optional), (2) warping, (3) blending, (4) Inpainting (optional).
To obtain high-quality results, it is recommended to select candidate input views properly. Therefore, the first step in RVS is an optional view selection. The n views the closest to the target image are selected in order to reduce the computation time. Otherwise, all the input images are used to create a new viewpoint.
The second step in RVS is the warping phase. Each input image is divided into a grid of triangles whose vertices are adjacent pixels (Figure 5a). Each of these vertices is reprojected to fit to the new camera pose and parameters (Figure 5b) and rasterized to avoid the cracks artifacts of Figure 3b. Then, each new triangle is given a score that will be used in the blending phase. This score describes the quality of a warped triangle—if the pixels lie on a disocclusion area, their triangle will be stretched and should hence be discarded from the final result (black areas in Figure 4-warping and Figure 5c). The remaining triangles are then rasterized according to their vertex color in the input image (Figure 5c). A depth test prioritizes the pixels with the lowest depth.
Figure 5.
Adjacent pixels of an input image (a) are grouped into triangles independently of their depth before being reprojected to their new image location (b). Triangles detected as lying on a disocclusion are discarded, resulting in a new warped image (c).
When the input images are warped to the target viewpoint, the results need to be blended into one single image. For a given pixel, the final output color c is the weighted mean of the color ci of each warped input:
c=1∑iwi∑iwiciE7
where wi is a weight representing the quality of a triangle [16], prioritizing foreground objects and highest quality triangles.
Finally, as shown in the inpainting of Figure 4, when multiple views are blended together, several occluded regions remain; if the occlusions are small enough, a basic inpainting process can be applied to remove them. Of course, the quality of the inpainting can compromise the overall image quality, hence, inpainting is not recommended. In RVS, the inpainting is not automatic but can be activated. In that case, the empty pixels take the color of the nearest non-empty pixel.
2.3.1 Non-Lambertian case
In the general case, DIBR uses depth maps to predict pixel displacement. However, a point on a non-Lambertian surface does not have a proper color (its color can rapidly change with a change in viewing direction); its appearance is a function of the surrounding scene, the normal at that point, and the index of refraction for refractive surfaces (see Figure 6). This not only makes depth estimation through stereo matching impossible but also implies that even with a correct depth map, the object cannot be rendered by a simple pixel shifting.
Figure 6.
The aspect of non-Lambertian objects is view dependent—Their surface does not appear the same color in each viewing direction.
Alternatively, to model the non-Lambertian surface in itself, it is possible to track its feature movements on the surface [29, 33, 34]. DIBR can be generalized to non-Lambertian objects by replacing the usual depth maps with the coefficients of a polynomial approximating the non-Lambertian features displacement [30, 31]. To clearly understand what this means, let us start with what happens for diffuse objects, where for a lateral camera movement xy, the new position uv of a pixel u0v0 is given by:
uv=u0v0+fDxy.E8
We extend this equation for non-Lambertian objects using polynomials:
uv=u0v0+PuxyPvxy,E9
with Puxy=∑i∑jaijxiyj and Pvxy=∑i∑jbijxiyj. Clearly, the diffuse case corresponds to a1,0=b0,1=fD and all other coefficients aij,bij set to zero.
Consequently, Eq. 9 approximates by a polynomial the nonlinear displacement of a refracted or reflected feature moving on non-Lambertian objects.
However, the polynomial expression rapidly diverges in extrapolation (e.g., when synthesizing a target view that is outside of the input images’ hull). The computed feature displacement becomes greater than the inverse of the non-Lambertian object’s depth, making the feature to be rendered outside of the non-Lambertian surface. This approximation is hence designed for interpolation and small extrapolation only.
Furthermore, these polynomials are not directly related to the physical reality of the non-Lambertian object. Hence, contrary to the simple relation linking the depth to the disparity of a diffuse object cf. Figure 2 and Eq. (1), the polynomials of Eq. (9) do not give the object geometry or the index of refraction.
The polynomial is rather designed to “track” non-Lambertian features that move nonlinearly across the input images. It nevertheless encounters the following limitations. For content with semi-transparent objects, the maps should be divided into several layers before applying the polynomial or depth image-based rendering. Scenes with glints and glossiness make it difficult to track features on their surfaces, often leading to a failure case of the proposed method.
3. Reference view synthesis (RVS) software
This section provides practical recommendations for the use of the reference view synthesizer (RVS) [14, 15, 16, 32, 35] (https://gitlab.com/mpeg-i-visual/rvs) developed as a DIBR-based view synthesizer for the MPEG immersive video (MIV) standard (https://mpeg-miv.org). Without further details on the compression and storage of immersive content [36], we give a comprehensive method to practically use the software on some test sequences (also provided to the MPEG community while developing RVS).
The following paragraphs give documentation on the image format, the axis system, and the data structure to synthesize new viewpoints from available ready-to-use datasets and/or new content users may provide.
3.1 Input images
RVS can accept any number of input images with depth maps, the only limitation being the computer memory. Each input color image must be provided along with its corresponding depth map.
3.1.1 Color images
The color images can be encoded on three RGB color channels, with 8-bit integers each, in any image format readable by OpenCV, for example, PNG or JPEG format.
Additionally, raw images in YUV can be used, with a bit depth of 8, 10, or 16 bits. In this case, multi-frame raw video can be used, applying the view synthesis on all specified frames.
3.1.2 Depth maps
The depth maps represent the depth coordinate of every point in the image following the forward axis of the camera. Similar to color images, they can be provided in different formats. They have to match the resolution of the input images, but they use only one channel.
The first option is to use the OpenEXR format. In that case, the software reads the depth value in float and uses it directly for reprojection.
In the case of integer coded formats, such as YUV or PNG, the precision can be set to 8, 10, or 16 bit per depth value—the bit depth. YUV files can be encoded in YUV420 or YUV400 format, only the Y channel being used. However, the quantization does not allow to directly use the integer as a depth value. Indeed, it would be impossible to use a depth map in meter units for objects in the range of a few meters or centimeters from the cameras.
To overcome this problem, the depth value is encoded into MPEG’s disparity format, mapping the closest object to 2bitdepth−1, and the farthest to 1. To obtain the actual depth value, first we divide the encoded depth map value by 2bitdepth−1 to obtain a value d in the range of 01, then remap the value in the range nf using:
d′=f×nn+d×f−n.E10
With n and f the near and far values of the scene and d′ the depth value lying in nf.
For very far objects, this equation is simplified (f ≥1000) to
d′=ndE11
The value 0 in the encoded depth maps is considered as invalid depth. It corresponds, for example, to disocclusions in a depth-sensing device-acquired map. Figure 7 shows an encoded depth map with invalid pixels and objects at different depths. Clearly, the foreground has high values, which corresponds to being a disparity value, that is, the inverse of a depth, cf. Eq. (11).
Figure 7.
Encoded depth map on integer values. Due to the shift between the color sensor and the depth sensor, the depth map reprojected to the color image misses some information, leaving invalid pixels, encoded on 0. The foreground objects are encoded on high disparities, while the background objects are encoded on low disparities.
In the case of polynomial maps for non-Lambertian objects, it is possible to encode up to degree 3 polynomials, hence 18 coefficients, and pass an additional depth map and mask for the non-Lambertian objects. Those coefficients are encoded similarly to the depth maps, using EXR (directly the float value) or YUV (normalized) format. The polynomial maps are numbered from 0 to 19 as follows.
with ai corresponding to the map i and bi to the map 10+i. The remaining map 9 is used to encode the depth map for Lambertian objects and the map 19 is used as a mask representing non-Lambertian objects (0 for Lambertian, 1 for non-Lambertian). The coefficients not used are left to 0. If the coefficients are encoded in YUV format, the depth (map n∘9) is normalized using Eq. 10, the mask (map n∘19) has 0 and 1 values and the other coefficients are linearly normalized between minimal m and maximal M values: ai′=M−mai+m.
3.2 Camera parameters
Additionally to the input images, the camera parameters must be known to create a novel view with DIBR and RVS. The extrinsic parameters describe the position and the rotation of the camera (Eq. 2), while the intrinsic parameters describe the projection matrix (Eq. 3). Perspective and equirectangular projections are also supported, requiring a slightly different description, as explained hereafter.
3.2.1 Extrinsic parameters
Common graphics processing software and APIs, such as Blender [37], COLMAP [38], OpenGL [39], Vulkan [40], specify their own coordinate system, often admitting different axes and directions, and different image coordinates. Transferring data from one application to the other requires then several coordinate transformation steps, which will be summarized here. We use the Omnidirectional Media Format (OMAF) [41] coordinate system of MPEG-I, combined with yaw-pitch-roll angles.
OMAF is the first industry standard for VR. It specifies the coordinate system used in VR applications, the projection and rectangular region-wise packing methods, the metadata storage, encapsulation, signaling, and streaming of omnidirectional data, and finally the media profiles and presentation profiles. For these reasons, it has been adopted in the camera configuration files of RVS.
The OMAF coordinate system is described in Figure 8. The axes are defined as follows:
X: Back-to-front, forward
Y: Lateral, left
Z: Vertical, up
Figure 8.
The omnidirectional media format coordinate system.
The rotations in degrees are defined with the Yaw-pitch-roll:
Yaw: Around the vertical axis
Pitch: Around the lateral axis
Roll: Around the back-to-front axis
A camera facing forward has all its rotation angles set to 0. The rotation matrix of the camera (world to camera) in our axis coordinate system is then given by:
R=RzyawRypitchRxrollE13
In order to transform a coordinate system from an application to OMAF, one needs to define the coordinate change matrix that matches the three axes, for example:
P=00−11000−10E14
This matrix sets x′y′z′(OMAF) = −zx−y(application), that is, it represents a coordinate system with the axes (left, down, backward). To transfer from this system to OMAF, we apply it to the rotation and position as follow:
R′=P.R.PTp′=P.pE15
where R′ and p′ are the rotation and position of the OMAF system, while R and p the rotation and position in the old coordinates.
The unit of the coordinate system does not have any prerequisite but must correspond to one of the depth maps.
RVS handles any number of input and target cameras, each of them can have its own parameters and projection types. In the case of a stereoscopic head-mounted display for VR, two target views – one for each eye – need to be synthesized with a relative position (interpupillary distance) corresponding to the eye distance, usually given by the headset’s framework along with the intrinsic parameters.
3.2.2 Intrinsic parameters
The intrinsic parameters can be defined for perspective or equirectangular projections. In both cases, the resolution needs to be specified.
For perspective projection, the input images need to be undistorted. In that way, only the focal length and the principal point need to be specified. Those values are in pixel units, the sensor size corresponding to the image resolution. The focals are given by fxfy, corresponding to the horizontal and vertical axis. The principal point ppxppy is defined from the top-left corner of the image as described in Figure 9(a). A principal point at the center of the image has a value of half the resolution. In the case of equirectangular projection (Figure 9b), the horizontal and vertical viewing range must be specified in degrees. For a full 360∘ panoramic image, the horizontal range is −180,180 and the vertical range is −9090. For a 180∘ image, the horizontal and vertical ranges are −9090.
Figure 9.
Intrinsic parameters of the camera for (a) a pinhole projection, (b) an equirectangular projection.
3.2.3 Camera file
The image specifications and camera parameters are specified in a json file with informative headers. An example with a perspective and an equirectangular camera is given here.
An optional parameter, DisplacementMethod, can be set to Polynomial instead of default parameter Depth to specify that, instead of a depth map (Eq. 10), RVS reads a displacement map (Eq. 12). In that case, similarly to the Depth_range, a Multi_depth_range can be specified for the polynomial coefficients in YUV format.
3.3 View synthesis file
In order to perform the view synthesis, an experiment setup file is created. It gives camera views specifications (which views to synthesize given the input viewpoints) in an easy to use json format. The file contains:
Input and target camera parameters file paths—path to the camera file described in the previous subsection. The same file can be used twice if all the input and target cameras are in the same file;
Input and target camera names matched with the camera names contained in the camera files. Any number of inputs and outputs can be specified;
Input images, output images, and depth maps file paths. In the case of polynomial maps, numbered from 0 to 19, the number is replaced by a *;
Number of output frames. Useful for uncompressed YUV video files. The synthesized number of frames can exceed the number of frames in the input videos by specifying an optional NumberOfOutputFrames. In that case, the video will be played back and forth until the desired number of frames is reached;
Precision: super-resolution factor to reach sub-pixel accuracy;
Colorspace: internal working color space, can be YUV or RGB. Following the color space used, the result may present small color variations;
Blending specifications: the method can be Simple (for CPU and GPU usage) or Multispectral (for CPU). Multispectral blending detects the borders in the images, to blend them with a hard threshold and therefore avoids ghosting. The factor represents the power on the weights of Eq. 7.
To test the view synthesis, we provide references to datasets that are provided with their cameras configuration json files. Publicly available datasets are available at the following addresses, while others have been provided as test scenes for MPEG-I immersive video exploration and standardization activities.
Toystable [42, 43]: a natural dataset with perspective cameras (Figure 10a) https://zenodo.org/record/5055542
Magritte [44, 45, 46, 47, 48]: a synthetic dataset with polynomial non-Lambertian maps (Figure 10b) https://zenodo.org/record/4488242, https://zenodo.org/record/5047238, https://zenodo.org/record/5047676, https://zenodo.org/record/5047769
Rabbit [49, 50]: the subaperture views of a multi-plenoptic camera dataset (Figure 10c) https://zenodo.org/record/5053770
Bear [51]: a natural dataset with perspective cameras with estimated and Lidar-sensed depth maps (Figure 10d): https://zenodo.org/record/5047463
MPEG test sequences (including [52, 53, 54, 55]): http://mpegx.int-evry.fr/mpegcontent/
Figure 10.
Overview of the open-source datasets. (a) Toystable consists of two camera arrays at 25 cm (5×5 cameras) and 55 cm (3×5 cameras) from the scene. (b) Magritte is a 21×21 camera array. (c) Rabbit is a 3×7 array of 5×5 subaperture images of a plenoptic camera. (d) Bear (4×8 cameras) is a dataset captured by a Lidar camera with estimated and sensed depth maps.
4. Displays
We provide in Figure 11 results obtained with the RVS software on various display types—autostereoscopic or light field screen (Courtesy ETRO-VUB, Belgium), holographic stereograms [56], and head-mounted displays. Additional videos can be found at the following links: https://youtu.be/ikJb9JaaE54 (holographic stereogram) and https://youtu.be/vavw-TcbHf4 (head-mounted-display).
Figure 11.
Instead of acquiring the 100 of views needed for the different kinds of display, RVS recreates them using four input images. (a) Autostereoscopic screen, (b) holographic stereogram, (c) head-mounted display.
Displaying a dynamic scene in VR requires real-time view synthesis, preferably at 90 frames per second and at a minimum of 30 frames per second for each eye. However, the processing time depends on the number of input images and their resolution – since their pixels form the mesh – resulting in different frame rates [16] (see Table 1). Using a NVIDIA GTX 1080TI GPU, around four input images at a full HD resolution can be processed to obtain a high visual quality while reaching real-time navigation.
The frame rate for view synthesis in VR depends on the number of input images and their resolution. The output images all have the resolution of oculus rift (i.e., 1080×1200 pixels). Those results have been obtained on a windows PC with Intel Xeon E5–2680@2.7GHz CPU and NVIDIA GTX 1080TI GPU.
In the case of the currently developed light field head-mounted display [57], the constraint is double—in addition to the real-time requirement, all the light rays reaching the user’s pupils need to be displayed to make the eye accommodation possible on the close objects, that is, not only one image per eye but all the micro-parallax views around the eye position are rendered.
4.1 Additional tools
In this section, we provide references for additional tools, which are not directly involved in the view synthesis but are nevertheless useful to prepare a dataset.
4.1.1 Camera calibration
The first step prior to DIBR is finding the camera parameters. Accurate intrinsic parameters, including distortion parameters, can be found using a calibration checkerboard-pattern, if the scene has a large enough baseline, or directly during the scene reconstruction (structure-from-motion (SfM) with the retrieval of intrinsic parameters). Using a pattern gives more accurate results but requires a supplementary preprocessing step. There exists open-source software such as Kalibr [58] and OpenCV [59] for camera calibration.
Extrinsic parameters of a set of cameras are retrieved using SfM, with or without the intrinsic parameters known as prior [60]. There exist many open-source software such as COLMAP [38] or AliceVision [61]. Those softwares calibrate the camera and automatically undistort the images.
4.1.2 Depth estimation
Besides parameters estimation, DIBR requires corresponding depth maps for each input view. If they are not acquired with a depth-sensing device, they can be computed using stereo-matching algorithms. Among many algorithms, Depth Estimation Reference Software (DERS) [62] and Immersive Video Depth Estimation (IVDE) [63, 64] are recognized by the MPEG-I community.
5. Conclusions
In this chapter, an overview of the main steps and frequent problems of view synthesis are described. By starting from sparse input pictures, we showed a DIBR method that renders the parallax effect on a multitude of displays, allowing a user to experience new aspects of multimedia immersion. In the second part, a description of how one can start experimenting with the state-of-the-art RVS software is thoroughly explained to avoid common pitfalls.
As research progresses, novel methods to create view synthesis emerge, such as NeRF, however, recent research results demonstrate that DIBR methods will still reach high-quality performances [16], in real time, that will be highly applicable in immersive applications, for example, in the context of MPEG immersive video.
Acknowledgments
This work was supported in part by the Fonds de la Recherche Scientifique – FNRS, Belgium, under Grant n·33679514, ColibriH; and in part by the HoviTron project that received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement N·951989 (https://www.hovitron.eu/).
Conflict of interest
The authors declare no conflict of interest.
Abbreviations
CPU
Central Processing Unit
DERS
Depth Estimation Reference Software
DIBR
Depth image-based rendering
GPU
Graphics Processing Unit
IVDE
Immersive Video Depth Estimation
MIV
MPEG Immersive Video
MPEG-I
Moving Picture Experts Group-Immersive
NeRF
Neural Radiance Field
OMAF
Omnidirectional Media Format
RGB
Red-Green-Blue format
RVS
Reference View Synthesizer
SfM
Structure-from-Motion
VR
Virtual Reality
YUV
Luminance-Chrominance format
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An overview of the DIBR approach and frequently encountered challenges (disocclusion and ghosting artifacts, multi-view blending, handling of non-Lambertian objects) are described. Such technology finds applications in VR immersive displays and holography. Finally, a comprehensive manual of the Reference View Synthesis software (RVS), an open-source tool tested on open datasets and recognized by the MPEG-I standardization activities (where “I” refers to “immersive”) is described for hands-on practicing.",reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/80515",risUrl:"/chapter/ris/80515",signatures:"Sarah Fachada, Daniele Bonatto, Mehrdad Teratani and Gauthier Lafruit",book:{id:"11192",type:"book",title:"Computer Game Development",subtitle:null,fullTitle:"Computer Game Development",slug:null,publishedDate:null,bookSignature:"Dr. Branislav Sobota",coverURL:"https://cdn.intechopen.com/books/images_new/11192.jpg",licenceType:"CC BY 3.0",editedByType:null,isbn:"978-1-80355-565-2",printIsbn:"978-1-80355-564-5",pdfIsbn:"978-1-80355-566-9",isAvailableForWebshopOrdering:!0,editors:[{id:"109378",title:"Dr.",name:"Branislav",middleName:null,surname:"Sobota",slug:"branislav-sobota",fullName:"Branislav Sobota"}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"}},authors:null,sections:[{id:"sec_1",title:"1. 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Burlingame, USA: Society for Imaging Science and Technology (IS&T) - Electronic Imaging; 2020'},{id:"B33",body:'Maeno K, Nagahara H, Shimada A, Taniguchi RI. Light Field Distortion Feature for Transparent Object Recognition. In: 2013 IEEE Conference on Computer Vision and Pattern Recognition. Portland, OR, USA: IEEE; 2013. pp. 2786-2793'},{id:"B34",body:'Xu Y, Nagahara H, Shimada A, Ri T. Transcut: Transparent object segmentation from a light-field image. Proceedings of the IEEE International Conference on Computer Vision, Santiago, Chile; 2015. pp. 3442-3450'},{id:"B35",body:'Bonatto D, Fachada S, Lafruit G. RVS kickstart: example test sequences and config files. Brussels, Belgium: ULB DI-fusion; 2019'},{id:"B36",body:'Lafruit G, Bonatto D, Tulvan C, Preda M, Yu L. Understanding MPEG-I Coding Standardization in Immersive VR/AR Applications. SMPTE Motion Imaging Journal. 2019;128(10):33-39'},{id:"B37",body:'Blender Online Community. Blender - A 3D Modelling and Rendering Package. Blender Institute, Amsterdam: Blender Foundation; 2021 Available from: http://www.blender.org'},{id:"B38",body:'Schonberger JL, Frahm JM. Structure-from-Motion Revisited. In: 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR). Las Vegas, NV, USA: IEEE; 2016. pp. 4104-4113'},{id:"B39",body:'Kessenich J, Baldwin D, Rost R. The OpenGL® Shading Language, Version 4.60.7, The Khronos Group Inc.; 2019'},{id:"B40",body:'Group TKVW. Vulkan® 1.2.202 - A Specification; 2021.12.07'},{id:"B41",body:'Omnidirectionnal Media Format. MPEG-I; 2021 Available from: https://mpeg.chiariglione.org/standards/mpeg-i/omnidirectional-media-format'},{id:"B42",body:'Bonatto D, Schenkel A, Lenertz T, Li Y, Lafruit G. ULB High Density 2D/3D Camera Array data set, version 2 [M41083]. ISO/IEC JTC1/SC29/WG11; 2017'},{id:"B43",body:'Bonatto D, Fachada S, Lafruit G. ULB ToysTable. Zenodo; 2021. 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Knowledge of the functional anatomy of the airway in these forms the basis of understanding the pathological conditions that may occur. The upper airway extends from the mouth to the trachea. It includes the mouth, the nose, the palate, the uvula, the pharynx, and the larynx. This section also describes the functional physiology of this airway. Managing the airway of a patient with craniofacial disorders poses many challenges to the anesthesiologist. Anatomical abnormalities may affect only intubation, only airway management, or both. 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This chapter consists of two sections. The first section will address the chemical and physical properties, pharmacokinetics and pharmacodynamics of the local anaesthetics. In the second section, examples of the commonly used doses and additives used for various peripheral and regional anaesthetics will be discussed. 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Correspondingly, anesthetic procedures in obese patients are also increasing due to both treatment of obesity and other surgical problems of obese patients. Anesthesia-related complications are also seen in obese patients than in normal-weighted population. The importance of anesthetic applications in obese patients originates from physiological and pharmacokinetic alterations. Inhalation of these patients via mask or intubation during general anesthesia may be difficult or even impossible. Determination of extubation time after awakening from anesthesia is also a critical decision. Sleep apnea syndrome and postoperative atelectasis are more common in obese patients than in normal-weighted population. Another vital complication that should be emphasized is thromboembolism, whose incidence and severity may be decreased by pharmacological and functional preventive modalities. This patient population has elevated risk of perioperative mortality and morbidity. Prior to any elective surgical procedure, an obese patient should be thoroughly evaluated to check medical conditions that may increase perioperative mortality risk. Since anesthesiologists will gradually encounter more obese patients, they need a better comprehending of the difficulties of obesity during anesthetic procedures and taking more preventive measures for their patients to avoid complications, or rendering them less traumatic, if any.",book:{id:"5490",slug:"current-topics-in-anesthesiology",title:"Current Topics in Anesthesiology",fullTitle:"Current Topics in Anesthesiology"},signatures:"Ismail Demirel, Esef Bolat and Aysun Yıldız Altun",authors:[{id:"191692",title:"Associate Prof.",name:"İsmail",middleName:null,surname:"Demirel",slug:"ismail-demirel",fullName:"İsmail Demirel"},{id:"191820",title:"Dr.",name:"Esef",middleName:null,surname:"Bolat",slug:"esef-bolat",fullName:"Esef Bolat"},{id:"191821",title:"Dr.",name:"Aysun",middleName:null,surname:"Yıldız Altun",slug:"aysun-yildiz-altun",fullName:"Aysun Yıldız Altun"}]},{id:"53159",doi:"10.5772/66574",title:"Postoperative Cognitive Dysfunction: Preclinical Highlights and Perspectives on Preventive Strategies",slug:"postoperative-cognitive-dysfunction-preclinical-highlights-and-perspectives-on-preventive-strategies",totalDownloads:1986,totalCrossrefCites:2,totalDimensionsCites:3,abstract:"One of the common complications associated with anaesthesia and surgery in geriatric patients is the postoperative cognitive dysfunction (POCD). This cognitive impairment affects the long-term prognosis and has been shown to be associated with long-term disability, higher health care costs, and even increased mortality. On the other hand, clinical research on POCD is in its infancy, the condition has not been clarified, and since no strategy for management is currently available, it is imperative to develop specific methods for prevention and management. Although its pathogenesis involves various factors, accumulating evidence suggests that surgery elicits an inflammatory response in the hippocampus, a brain area closely related to cognitive function, playing a key role in the development of POCD. Several studies suggest that age-related phenotypic change of microglia is associated with pathogenic neuroinflammation, and more importantly it may be modifiable. In this chapter, we discuss the current overview and preclinical highlights regarding POCD. We further discuss some perspectives on preventive strategies for POCD, based on the findings of our preclinical research and the available literature.",book:{id:"5490",slug:"current-topics-in-anesthesiology",title:"Current Topics in Anesthesiology",fullTitle:"Current Topics in Anesthesiology"},signatures:"Fabricio M. Locatelli and Takashi Kawano",authors:[{id:"169688",title:"Dr.",name:"Takashi",middleName:null,surname:"Kawano",slug:"takashi-kawano",fullName:"Takashi Kawano"},{id:"191676",title:"Dr.",name:"Fabricio",middleName:null,surname:"Locatelli",slug:"fabricio-locatelli",fullName:"Fabricio Locatelli"}]}],mostDownloadedChaptersLast30Days:[{id:"65467",title:"Anesthesia Management for Large-Volume Liposuction",slug:"anesthesia-management-for-large-volume-liposuction",totalDownloads:6204,totalCrossrefCites:1,totalDimensionsCites:2,abstract:"The apparent easiness with which liposuction is performed favors that patients, young surgeons, and anesthesiologists without experience in this field ignore the many events that occur during this procedure. Liposuction is a procedure to improve the body contour and not a surgery to reduce weight, although recently people who have failed in their plans to lose weight look at liposuction as a means to contour their body figure. Tumescent liposuction of large volumes requires a meticulous selection of each patient; their preoperative evaluation and perioperative management are essential to obtain the expected results. The various techniques of general anesthesia are the most recommended and should be monitored in the usual way, as well as monitoring the total doses of infiltrated local anesthetics to avoid systemic toxicity. The management of intravenous fluids is controversial, but the current trend is the restricted use of hydrosaline solutions. The most feared complications are deep vein thrombosis, pulmonary thromboembolism, fat embolism, lung edema, hypothermia, infections and even death. The adherence to the management guidelines and prophylaxis of venous thrombosis/thromboembolism is mandatory.",book:{id:"6221",slug:"anesthesia-topics-for-plastic-and-reconstructive-surgery",title:"Anesthesia Topics for Plastic and Reconstructive Surgery",fullTitle:"Anesthesia Topics for Plastic and Reconstructive Surgery"},signatures:"Sergio Granados-Tinajero, Carlos Buenrostro-Vásquez, Cecilia\nCárdenas-Maytorena and Marcela Contreras-López",authors:[{id:"273532",title:"Dr.",name:"Sergio Octavio",middleName:null,surname:"Granados Tinajero",slug:"sergio-octavio-granados-tinajero",fullName:"Sergio Octavio Granados Tinajero"}]},{id:"53389",title:"Anesthesia for Urological Surgery",slug:"anesthesia-for-urological-surgery",totalDownloads:3603,totalCrossrefCites:0,totalDimensionsCites:1,abstract:"Because of the variable techniques and patients’ positions used in urological surgery, anesthesia for urologic surgery requires advanced knowledge and special transactions. In this matter, it is important to follow current approaches for anesthesiologists. Different surgical procedures and complications due to different positions or anesthesia were evaluated separately to be more concise. We have researched recent literature and created this chapter about new technologies in urological surgery and development in anesthesia for urological surgery.",book:{id:"5490",slug:"current-topics-in-anesthesiology",title:"Current Topics in Anesthesiology",fullTitle:"Current Topics in Anesthesiology"},signatures:"Zeki Tuncel Tekgül, Burcu Özalp Horsanali and Mustafa Ozan\nHorsanali",authors:[{id:"59702",title:"Dr.",name:"Mustafa Ozan",middleName:null,surname:"Horsanali",slug:"mustafa-ozan-horsanali",fullName:"Mustafa Ozan Horsanali"},{id:"190164",title:"Dr.",name:"Zeki Tuncel",middleName:null,surname:"Tekgül",slug:"zeki-tuncel-tekgul",fullName:"Zeki Tuncel Tekgül"},{id:"195091",title:"Dr.",name:"Burcu Özalp",middleName:null,surname:"Horsanalı",slug:"burcu-ozalp-horsanali",fullName:"Burcu Özalp Horsanalı"}]},{id:"61712",title:"Functional Anatomy and Physiology of Airway",slug:"functional-anatomy-and-physiology-of-airway",totalDownloads:3783,totalCrossrefCites:1,totalDimensionsCites:5,abstract:"In this chapter, we scope the importance of functional anatomy and physiology of the upper airway. The upper airway has an important role in transporting air to the lungs. Both the anatomical structure of the airways and the functional properties of the mucosa, cartilages, and neural and lymphatic tissues influence the characteristics of the air that is inhaled. The airway changes in size, shape, and position throughout its development from the neonate to the adults. Knowledge of the functional anatomy of the airway in these forms the basis of understanding the pathological conditions that may occur. The upper airway extends from the mouth to the trachea. It includes the mouth, the nose, the palate, the uvula, the pharynx, and the larynx. This section also describes the functional physiology of this airway. Managing the airway of a patient with craniofacial disorders poses many challenges to the anesthesiologist. Anatomical abnormalities may affect only intubation, only airway management, or both. This section also focuses on the abnormal airways in obesity, pregnancy, children and neonate, and patients with abnormal facial defects.",book:{id:"6495",slug:"tracheal-intubation",title:"Tracheal Intubation",fullTitle:"Tracheal Intubation"},signatures:"Aslı Mete and İlknur Hatice Akbudak",authors:[{id:"237495",title:"Dr.",name:"Asli",middleName:null,surname:"Mete",slug:"asli-mete",fullName:"Asli Mete"},{id:"237882",title:"Dr.",name:"Ilknur",middleName:"Hatice",surname:"Akbudak",slug:"ilknur-akbudak",fullName:"Ilknur Akbudak"}]},{id:"60582",title:"Indications for Endotracheal Intubation",slug:"indications-for-endotracheal-intubation",totalDownloads:3721,totalCrossrefCites:1,totalDimensionsCites:0,abstract:"Endotracheal intubation may be required when respiratory distress or airway integrity cannot be achieved or maintained for any reason. It should be considered that intubation may be required when evaluating the patient, and that in the long term, airway protection will be needed or that the problem cannot be solved by noninvasive ventilation via airway aids and devices. Identifying the problem causing the patient’s respiratory failure helps in making the decision to intubate. In fact, the clinician must be fast and self-confident when deciding on intubation. It is difficult to decide in some complex situations. It is very important to evaluate the patient, according to clinical status, age, and comorbidity, and to determine urgent intubation need. In non-diagnostic cases, further research is needed to investigate the causes of the condition such as hypoxia/hypercapnia resulting in patient respiratory distress. Different voice tone, swallowing difficulties, coughing attacks, stridor, dyspnea can be a sign of upper airway obstruction. Arterial blood gas analysis will facilitate our decision to make intubation. Non-invasive pulse oximetry and continuous capnography values may also be a guide, but the most important thing is that delayed intubation decision may bring life-threatening situations.",book:{id:"6495",slug:"tracheal-intubation",title:"Tracheal Intubation",fullTitle:"Tracheal Intubation"},signatures:"Yeliz Şahiner",authors:[{id:"236458",title:"Dr.",name:"Yeliz",middleName:null,surname:"Şahiner",slug:"yeliz-sahiner",fullName:"Yeliz Şahiner"}]},{id:"64750",title:"Perioperative Complications in Plastic Surgery",slug:"perioperative-complications-in-plastic-surgery",totalDownloads:1424,totalCrossrefCites:0,totalDimensionsCites:0,abstract:"Anesthetic complications in the perioperative period in plastic surgery are extremely rare, although they can be catastrophic and sometimes fatal. The proper selection and correct preoperative assessment of patients are the key to stay away from unwanted events. Preanesthesia evaluation is mandatory in each patient and must include clinical history, complete physical examination, and routine and special laboratory tests in patients with associated pathologies. Anesthetic management is based on these results, type of surgery, experience of the anesthesiologist, and the operating environment. The anesthetic technique can be local, regional, or general with standard noninvasive monitoring. It is recommended that an anesthesiologist be present in all plastic surgery procedures. Complications are usually the result of moving away from the guidelines already established for an excellent practice or the result of sentinel events rather than human errors. Pulmonary embolism is probably the most feared complication, with soft tissue infections being the most frequent complication in plastic surgery. Less common complications include arrhythmias, overhydration, allergies, bleeding, skin necrosis, dehiscence of wounds, brain damage, and dead. Anesthesiologists, surgeons, nurses, and all personnel involved in the care of these patients must work as a team of highly qualified and updated professionals.",book:{id:"6221",slug:"anesthesia-topics-for-plastic-and-reconstructive-surgery",title:"Anesthesia Topics for Plastic and Reconstructive Surgery",fullTitle:"Anesthesia Topics for Plastic and Reconstructive Surgery"},signatures:"Víctor M. Whizar-Lugo, Jaime Campos-León and Alejandro\nMoreno-Guillen",authors:[{id:"169249",title:"Prof.",name:"Víctor M.",middleName:null,surname:"Whizar-Lugo",slug:"victor-m.-whizar-lugo",fullName:"Víctor M. Whizar-Lugo"},{id:"170821",title:"Dr.",name:"Jaime",middleName:null,surname:"Campos-León",slug:"jaime-campos-leon",fullName:"Jaime Campos-León"}]}],onlineFirstChaptersFilter:{topicId:"1139",limit:6,offset:0},onlineFirstChaptersCollection:[],onlineFirstChaptersTotal:0},preDownload:{success:null,errors:{}},subscriptionForm:{success:null,errors:{}},aboutIntechopen:{},privacyPolicy:{},peerReviewing:{},howOpenAccessPublishingWithIntechopenWorks:{},sponsorshipBooks:{sponsorshipBooks:[],offset:0,limit:8,total:null},allSeries:{pteSeriesList:[{id:"14",title:"Artificial Intelligence",numberOfPublishedBooks:9,numberOfPublishedChapters:90,numberOfOpenTopics:6,numberOfUpcomingTopics:0,issn:"2633-1403",doi:"10.5772/intechopen.79920",isOpenForSubmission:!0},{id:"7",title:"Biomedical Engineering",numberOfPublishedBooks:12,numberOfPublishedChapters:108,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2631-5343",doi:"10.5772/intechopen.71985",isOpenForSubmission:!0}],lsSeriesList:[{id:"11",title:"Biochemistry",numberOfPublishedBooks:33,numberOfPublishedChapters:330,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2632-0983",doi:"10.5772/intechopen.72877",isOpenForSubmission:!0},{id:"25",title:"Environmental Sciences",numberOfPublishedBooks:1,numberOfPublishedChapters:19,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2754-6713",doi:"10.5772/intechopen.100362",isOpenForSubmission:!0},{id:"10",title:"Physiology",numberOfPublishedBooks:14,numberOfPublishedChapters:145,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2631-8261",doi:"10.5772/intechopen.72796",isOpenForSubmission:!0}],hsSeriesList:[{id:"3",title:"Dentistry",numberOfPublishedBooks:9,numberOfPublishedChapters:141,numberOfOpenTopics:2,numberOfUpcomingTopics:0,issn:"2631-6218",doi:"10.5772/intechopen.71199",isOpenForSubmission:!0},{id:"6",title:"Infectious Diseases",numberOfPublishedBooks:13,numberOfPublishedChapters:123,numberOfOpenTopics:4,numberOfUpcomingTopics:0,issn:"2631-6188",doi:"10.5772/intechopen.71852",isOpenForSubmission:!0},{id:"13",title:"Veterinary Medicine and Science",numberOfPublishedBooks:11,numberOfPublishedChapters:112,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2632-0517",doi:"10.5772/intechopen.73681",isOpenForSubmission:!0}],sshSeriesList:[{id:"22",title:"Business, Management and Economics",numberOfPublishedBooks:1,numberOfPublishedChapters:22,numberOfOpenTopics:3,numberOfUpcomingTopics:0,issn:"2753-894X",doi:"10.5772/intechopen.100359",isOpenForSubmission:!0},{id:"23",title:"Education and Human Development",numberOfPublishedBooks:0,numberOfPublishedChapters:11,numberOfOpenTopics:1,numberOfUpcomingTopics:1,issn:null,doi:"10.5772/intechopen.100360",isOpenForSubmission:!0},{id:"24",title:"Sustainable Development",numberOfPublishedBooks:1,numberOfPublishedChapters:19,numberOfOpenTopics:5,numberOfUpcomingTopics:0,issn:"2753-6580",doi:"10.5772/intechopen.100361",isOpenForSubmission:!0}],testimonialsList:[{id:"13",text:"The collaboration with and support of the technical staff of IntechOpen is fantastic. 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",coverUrl:"https://cdn.intechopen.com/series/covers/22.jpg",latestPublicationDate:"August 12th, 2022",hasOnlineFirst:!0,numberOfPublishedBooks:1,editor:{id:"356540",title:"Prof.",name:"Taufiq",middleName:null,surname:"Choudhry",slug:"taufiq-choudhry",fullName:"Taufiq Choudhry",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y000036X2hvQAC/Profile_Picture_2022-03-14T08:58:03.jpg",biography:"Prof. Choudhry holds a BSc degree in Economics from the University of Iowa, as well as a Masters and Ph.D. in Applied Economics from Clemson University, USA. In January 2006, he became a Professor of Finance at the University of Southampton Business School. He was previously a Professor of Finance at the University of Bradford Management School. He has over 80 articles published in international finance and economics journals. His research interests and specialties include financial econometrics, financial economics, international economics and finance, housing markets, financial markets, among others.",institutionString:null,institution:{name:"University of Southampton",institutionURL:null,country:{name:"United Kingdom"}}},editorTwo:null,editorThree:null},subseries:{paginationCount:3,paginationItems:[{id:"86",title:"Business and Management",coverUrl:"https://cdn.intechopen.com/series_topics/covers/86.jpg",isOpenForSubmission:!0,editor:{id:"128342",title:"Prof.",name:"Vito",middleName:null,surname:"Bobek",slug:"vito-bobek",fullName:"Vito Bobek",profilePictureURL:"https://mts.intechopen.com/storage/users/128342/images/system/128342.jpg",biography:"Dr. Vito Bobek works as an international management professor at the University of Applied Sciences FH Joanneum, Graz, Austria. He has published more than 400 works in his academic career and visited twenty-two universities worldwide as a visiting professor. Dr. Bobek is a member of the editorial boards of six international journals and a member of the Strategic Council of the Minister of Foreign Affairs of the Republic of Slovenia. He has a long history in academia, consulting, and entrepreneurship. His own consulting firm, Palemid, has managed twenty significant projects, such as Cooperation Program Interreg V-A (Slovenia-Austria) and Capacity Building for the Serbian Chamber of Enforcement Agents. He has also participated in many international projects in Italy, Germany, Great Britain, the United States, Spain, Turkey, France, Romania, Croatia, Montenegro, Malaysia, and China. Dr. Bobek is also a co-founder of the Academy of Regional Management in Slovenia.",institutionString:"Universities of Applied Sciences FH Joanneum, Austria",institution:{name:"Universities of Applied Sciences Joanneum",institutionURL:null,country:{name:"Austria"}}},editorTwo:{id:"293992",title:"Dr.",name:"Tatjana",middleName:null,surname:"Horvat",slug:"tatjana-horvat",fullName:"Tatjana Horvat",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002hXb0hQAC/Profile_Picture_1642419002203",biography:"Tatjana Horvat works as a professor for accountant and auditing at the University of Primorska, Slovenia. She is a Certified State Internal Auditor (licensed by Ministry of Finance RS) and Certified Internal Auditor for Business Sector and Certified accountant (licensed by Slovenian Institute of Auditors). At the Ministry of Justice of Slovenia, she is a member of examination boards for court expert candidates and judicial appraisers in the following areas: economy/finance, valuation of companies, banking, and forensic investigation of economic operations/accounting. At the leading business newspaper Finance in Slovenia (Swedish ownership), she is the editor and head of the area for business, finance, tax-related articles, and educational programs.",institutionString:null,institution:{name:"University of Primorska",institutionURL:null,country:{name:"Slovenia"}}},editorThree:null},{id:"87",title:"Economics",coverUrl:"https://cdn.intechopen.com/series_topics/covers/87.jpg",isOpenForSubmission:!0,editor:{id:"327730",title:"Prof.",name:"Jaime",middleName:null,surname:"Ortiz",slug:"jaime-ortiz",fullName:"Jaime Ortiz",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00002zaOKZQA2/Profile_Picture_1642145584421",biography:"Dr. Jaime Ortiz holds degrees from Chile, the Netherlands, and the United States. He has held tenured faculty, distinguished professorship, and executive leadership appointments in several universities around the world. Dr. Ortiz has previously worked for international organizations and non-government entities in economic and business matters, and he has university-wide globalization engagement in more than thirty-six countries. He has advised, among others, the United Nations Development Program, Inter-American Development Bank, Organization of American States, Pre-investment Organization of Latin America and the Caribbean, Technical Cooperation of the Suisse Government, and the World Bank. Dr. Ortiz is the author, co-author, or editor of books, book chapters, textbooks, research monographs and technical reports, and refereed journal articles. He is listed in Who’s Who in the World, Who’s Who in America, Who’s Who in Finance and Business, Who’s Who in Business Higher Education, Who’s Who in American Education, and Who’s Who Directory of Economists. Dr. Ortiz has been a Fulbright Scholar and an MSI Leadership Fellow with the W.K. Kellogg Foundation. His teaching interests revolve around global economies and markets while his research focuses on topics related to development and growth, global business decisions, and the economics of technical innovation.",institutionString:null,institution:{name:"University of Houston",institutionURL:null,country:{name:"United States of America"}}},editorTwo:null,editorThree:null},{id:"88",title:"Marketing",coverUrl:"https://cdn.intechopen.com/series_topics/covers/88.jpg",isOpenForSubmission:!0,editor:{id:"203609",title:"Associate Prof.",name:"Hanna",middleName:null,surname:"Gorska-Warsewicz",slug:"hanna-gorska-warsewicz",fullName:"Hanna Gorska-Warsewicz",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bSD9pQAG/Profile_Picture_2022-06-14T11:58:32.jpeg",biography:"Hanna Górska-Warsewicz, Ph.D. is Associate Professor at Warsaw University of Life Sciences and Head of Department of Food Market and Consumption Research. She specializes in the subject of brands, brand equity, and brand management in production, service, and trade enterprises. She combines this subject with marketing and marketing management in both theoretical and practical aspects. Prof. Hanna Górska-Warsewicz also analyzes brands in the context of trademarks, legal regulations and the protection of intangible. She is an author or co-author of over 200 publications in this field, including 8 books. She works with the business sector and has participated in projects for the Ministry of Agriculture and Rural Development and the Ministry of Education and Science in Poland.",institutionString:null,institution:{name:"Warsaw University of Life Sciences",institutionURL:null,country:{name:"Poland"}}},editorTwo:null,editorThree:null}]},overviewPageOFChapters:{paginationCount:11,paginationItems:[{id:"83075",title:"Practices and Challenges of Community Services at Debre Markos University, Ethiopia: A Case Study",doi:"10.5772/intechopen.105896",signatures:"Adane Mengist",slug:"practices-and-challenges-of-community-services-at-debre-markos-university-ethiopia-a-case-study",totalDownloads:1,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"Corporate Social Responsibility",coverURL:"https://cdn.intechopen.com/books/images_new/11602.jpg",subseries:{id:"86",title:"Business and Management"}}},{id:"82858",title:"Corporate Social Responsibility a Case of the Provision of Recreational Facilities",doi:"10.5772/intechopen.105608",signatures:"Peter Musa Wash, Shida Irwana Omar, Badaruddin Mohamed and Mohd Ismail Isa",slug:"corporate-social-responsibility-a-case-of-the-provision-of-recreational-facilities",totalDownloads:5,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"Corporate Social Responsibility",coverURL:"https://cdn.intechopen.com/books/images_new/11602.jpg",subseries:{id:"86",title:"Business and Management"}}},{id:"82786",title:"Discussion of Purchasing Virtual Digital Nature and Tourism",doi:"10.5772/intechopen.105869",signatures:"Hiroko Oe and Yasuyuki Yamaoka",slug:"discussion-of-purchasing-virtual-digital-nature-and-tourism",totalDownloads:7,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"A New Era of Consumer Behavior - Beyond the Pandemic",coverURL:"https://cdn.intechopen.com/books/images_new/11581.jpg",subseries:{id:"88",title:"Marketing"}}},{id:"82289",title:"Consumer Culture and Abundance of Choices: Having More, Feeling Blue",doi:"10.5772/intechopen.105607",signatures:"Ondřej Roubal",slug:"consumer-culture-and-abundance-of-choices-having-more-feeling-blue",totalDownloads:7,totalCrossrefCites:0,totalDimensionsCites:0,authors:null,book:{title:"A New Era of Consumer Behavior - Beyond the Pandemic",coverURL:"https://cdn.intechopen.com/books/images_new/11581.jpg",subseries:{id:"88",title:"Marketing"}}}]},overviewPagePublishedBooks:{paginationCount:1,paginationItems:[{type:"book",id:"11392",title:"Leadership in a Changing World",subtitle:"A Multidimensional Perspective",coverURL:"https://cdn.intechopen.com/books/images_new/11392.jpg",slug:"leadership-in-a-changing-world-a-multidimensional-perspective",publishedDate:"May 11th 2022",editedByType:"Edited by",bookSignature:"Muhammad Mohiuddin, Bilal Khalid, Md. 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