This textbook offers advanced content on computer vision (basic content can be found in its prerequisite textbook, "2D Computer Vision: Principles, Algorithms and Applications"), including the basic principles, typical methods and practical techniques. It is intended for graduate courses on related topics, e.g. Computer Vision, 3-D Computer Vision, Graphics, Artificial Intelligence, etc. The book is mainly based on my lecture notes for several undergraduate and graduate classes I have offered over the past several years, while a number of topics stem from my research publications co-authored…mehr
This textbook offers advanced content on computer vision (basic content can be found in its prerequisite textbook, "2D Computer Vision: Principles, Algorithms and Applications"), including the basic principles, typical methods and practical techniques. It is intended for graduate courses on related topics, e.g. Computer Vision, 3-D Computer Vision, Graphics, Artificial Intelligence, etc. The book is mainly based on my lecture notes for several undergraduate and graduate classes I have offered over the past several years, while a number of topics stem from my research publications co-authored with my students. This book takes into account the needs of learners with various professional backgrounds, as well as those of self-learners. Furthermore, it can be used as a reference guide for practitioners and professionals in related fields.
To aid in comprehension, the book includes a wealth of self-test questions (with hints and answers). On the one hand, these questions help teachers to carry out online teaching and interact with students during lectures; on the other, self-learners can use them to assess whether they have grasped the key content.
Yu-Jin ZHANG received his Ph.D. in Applied Science from the State University of Liège, Liège, Belgium, in 1989. From 1989 to 1993, he was a postdoctoral fellow and research fellow at the Delft University of Technology, Delft, the Netherlands. In 1993, he joined the Department of Electronic Engineering, Tsinghua University, Beijing, China, where he has been a Professor (since 1997) and tenured Professor (since 2014) of Image Engineering. He is active in education on and research into image engineering (including image processing, image analysis, and image understanding) and has published more than 550 research papers and more than 50 books in this field. He has served as program chair of the ¿Twenty-Fourth International Conference on Image Processing (ICIP¿2017)¿ and several other international conferences. He is the Honorary Chairman of Supervisors (since 2020) of CSIG, a Fellow of SPIE (since 2011) and a Fellow of CSIG (since 2019).
Inhaltsangabe
Chapter 1. Introduction.- Chapter 2. Camera Calibration.- Chapter 3. 3-D Image Acquisition.- Chapter 4. Video and Motion Information.- Chapter 5. Moving Object Detection and Tracking.- Chapter 6. Binocular Stereo Vision.- Chapter 7. Monocular Multiple Image Reconstruction.- Chapter 8. Monocular Single Image Reconstruction.- Chapter 9. 3-D Scene Representation.- Chapter 10. Scene Matching.- Chapter 11. Knowledge and Scene Interpretation.- Chapter 12. Spatial-Temporal Behavior Understanding.