Omnidirectional Vision From Theory To

Omnidirectional cameras, vision sensors that can capture 360° images, have in recent years had growing success in computer vision, robotics and the entertainment industry. In fact, modern omnidirectional cameras are compact, lightweight and inexpensive, and are thus being integrated in an increasing number of robotic platforms and consumer devices. However, the special format of output data requires tools that are appropriate for camera calibration, signal analysis and image interpretation.

This book is divided into six chapters written by world-renowned scholars. In a rigorous yet accessible way, the mathematical foundation of omnidirectional vision is presented, from image geometry and camera calibration to image processing for central and non-central panoramic systems. Special emphasis is given to fisheye cameras and catadioptric systems, which combine mirrors with lenses. The main applications of omnidirectional vision, including 3D scene reconstruction and robot localization and navigation, are also surveyed. Finally, the recent trend towards AI-infused methods (deep learning architectures) and other emerging research directions are discussed.

Pascal Vasseur is Full Professor at the University of Picardie Jules Verne, France, and a member of the MIS laboratory. He is the head of the Department of Informatics. His research interests include computer vision and image processing and their applications in intelligent transportation systems and mobile robotics.

Fabio Morbidi is Associate Professor at the University of Picardie Jules Verne, France, and a member of the MIS laboratory. He is an IEEE senior member and currently serves as an associate editor for the IEEE Transactions on Robotics. His research interests include network systems and robotic vision.