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.
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"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.
Computer vision.
Image processing.
Computer algorithms.
006
.
37
23
TA1634
.
S97
2022
Szeliski, Richard,
1958-
کتابخانه مرکزی و مرکز اطلاع رسانی دانشگاه
20231014080456.0
rda
Computer Vision Algorithms and Applications (Texts in Computer Science)-Springer (2022).pdf