About the book
Object detection, tracking, and recognition in images are key challenges in computer vision. Object detection deals with detecting instances of semantic objects such as humans, buildings, cars, etc. Object detection has applications in many areas of computer vision, including image retrieval, face detection, and video surveillance. Using any type of digital image you have to detect all objects (a restricted class of objects depend on your dataset). Object recognition is a general term to describe a collection of related computer vision tasks that involve identifying objects.
Four computer vision tasks are:
- Image Classification – type or class of an object in an image prediction;
- Object Localization – the presence of objects in an image location and indication of their location with a bounding box;
- Object Detection – the presence of objects with a bounding box location and types or classes of the located objects in an image;
- Object Segmentation – recognized objects instances indication by highlighting the specific pixels of the object instead of a coarse bounding box.
This book provides the reader with a balanced approach between the theory and practice of selected methods in these areas to make the book accessible to a range of researchers, engineers, developers and postgraduate students working in computer vision and related fields.