Peter Corcoran

National University of Ireland, GalwayIreland

Peter Corcoran received the BAI (Electronic Engineering) and BA (Math’s) degrees from Trinity College Dublin in 1984. He continued his studies at TCD and was awarded a Ph.D. in Electronic Engineering for research work in the field of Dielectric Liquids. In 1986 he was appointed to a lectureship in Electronic Engineering at the National University of Ireland Galway. He is currently vice-dean in the College of Engineering & Informatics at NUI, Galway. His research interests include embedded systems applications, home networking, digital imaging, pattern recognition, face & fingerprint biometrics, smart grid and wired and wireless networking technologies. He was technical and conference chair of the IEEE International Conference on Consumer Electronics (ICCE) in 2010 and 2011 respectively. He is also editor of the IEEE Consumer Electronics Society newsletter and Editor-in-Chief of the newly launched (2012) IEEE Consumer Electronics Magazine. Peter is also a co-founder of FotoNation, a leading OEM supplier of in-camera image processing and analysis software, including embedded solutions for red-eye detection & correction and face tracking and recognition. Fotonation is now part of the Imaging and Optics division of Tessera Technologies. He is author of more than 200 technical publications and co-inventor on more than 100 granted US patents. He is a Fellow of the IEEE.

1books edited

Latest work with IntechOpen by Peter Corcoran

As a baby one of our earliest stimuli is that of human faces. We rapidly learn to identify, characterize and eventually distinguish those who are near and dear to us. We accept face recognition later as an everyday ability. We realize the complexity of the underlying problem only when we attempt to duplicate this skill in a computer vision system. This book is arranged around a number of clustered themes covering different aspects of face recognition. The first section on Statistical Face Models and Classifiers presents reviews and refinements of some well-known statistical models. The next section presents two articles exploring the use of Infrared imaging techniques and is followed by few articles devoted to refinements of classical methods. New approaches to improve the robustness of face analysis techniques are followed by two articles dealing with real-time challenges in video sequences. A final article explores human perceptual issues of face recognition.

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