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.

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.