Processing, Analyzing and Learning of Images, Shapes, and Forms: Part 1
Nonfiction, Science & Nature, Mathematics, Mathematical Analysis, Science, Earth Sciences, Geology
| Author: | Ron Kimmel, Xue-Cheng Tai | ISBN: | 9780444642066 |
| Publisher: | Elsevier Science | Publication: | November 8, 2018 |
| Imprint: | North Holland | Language: | English |
| Author: | Ron Kimmel, Xue-Cheng Tai |
| ISBN: | 9780444642066 |
| Publisher: | Elsevier Science |
| Publication: | November 8, 2018 |
| Imprint: | North Holland |
| Language: | English |
Processing, Analyzing and Learning of Images, Shapes, and Forms: Volume 19, Part One provides a comprehensive survey of the contemporary developments related to the analysis and learning of images, shapes and forms. It covers mathematical models as well as fast computational techniques, and includes new chapters on Alternating diffusion: a geometric approach for sensor fusion, Shape Correspondence and Functional Maps, Geometric models for perception-based image processing, Decomposition schemes for nonconvex composite minimization: theory and applications, Low rank matrix recovery: algorithms and theory, Geometry and learning for deformation shape correspondence, and Factoring scene layout from monocular images in presence of occlusion.
- Presents a contemporary view on the topic, comprehensively covering the newest developments and content
- Provides a comprehensive survey of the contemporary developments related to the analysis and learning of images, shapes and forms
Processing, Analyzing and Learning of Images, Shapes, and Forms: Volume 19, Part One provides a comprehensive survey of the contemporary developments related to the analysis and learning of images, shapes and forms. It covers mathematical models as well as fast computational techniques, and includes new chapters on Alternating diffusion: a geometric approach for sensor fusion, Shape Correspondence and Functional Maps, Geometric models for perception-based image processing, Decomposition schemes for nonconvex composite minimization: theory and applications, Low rank matrix recovery: algorithms and theory, Geometry and learning for deformation shape correspondence, and Factoring scene layout from monocular images in presence of occlusion.
- Presents a contemporary view on the topic, comprehensively covering the newest developments and content
- Provides a comprehensive survey of the contemporary developments related to the analysis and learning of images, shapes and forms
