Previous edition: 2011

Includes bibliographical references and index

Introduction -- Image formation -- Image processing -- Model fitting and optimization -- Deep learning -- Recognition -- Feature detection and matching -- Image alignment and stitching -- Motion estimation -- Computational photography -- Structure from motion and SLAM -- Depth estimation -- 3D reconstruction -- Image-based rendering -- Conclusion -- Appendix A: Linear algebra -- Appendix B: Bayesian modeling and inference -- Appendix C: Supplementary material

"Computer Vision: Algorithms and Applications explores the variety of techniques used to analyze and interpret images. It also describes challenging real-world applications where vision is being successfully used, both in specialized applications such as image search and autonomous navigation, as well as for fun, consumer-level tasks that students can apply to their own personal photos and videos. More than just a source of "recipes," this exceptionally authoritative and comprehensive textbook/reference takes a scientific approach to the formulation of computer vision problems. These problems are then analyzed using the latest classical and deep learning models and solved using rigorous engineering principles."--Page 4 of cover