Computer Vision Metrics Krig, Scott

Based on the successful 2014 book published by Apress, this textbook edition is expanded to provide a comprehensive history and state-of-the-art survey for fundamental computer vision methods. With over 800 essential references, as well as chapter-by-chapter learning assignments, both students and researchers can dig deeper into core computer vision topics.

Based on the successful 2014 book published by Apress, this textbook edition is expanded to provide a comprehensive history and state-of-the-art survey for fundamental computer vision methods. With over 800 essential references, as well as chapter-by-chapter learning assignments, both students and researchers can dig deeper into core computer vision topics.
The survey covers everything from feature descriptors, regional and global feature metrics, feature learning architectures, deep learning, neuroscience of vision, neural networks, and detailed example architectures to illustrate computer vision hardware and software optimization methods.

Based on the successful 2014 book published by Apress, this textbook edition is expanded to provide a comprehensive history and state-of-the-art survey for fundamental computer vision methods. With over 800 essential references, as well as chapter-by-chapter learning assignments, both students and researchers can dig deeper into core computer vision topics.

Computer Vision Metrics provides an extensive survey and analysis of over 100 current and historical feature description and machine vision methods, with a detailed taxonomy for local, regional and global features.