Foundations of Computer Vision - Adaptive Computation and Machine Learning Series

An accessible, authoritative, and up-to-date computer vision textbook offering a comprehensive introduction to the foundations of the field that incorporates the latest deep learning advances. Machine learning has revolutionized computer vision, but the methods of today have deep roots in the history of the field. Providing a much-needed modern treatment, this accessible and up-to-date textbook comprehensively introduces the foundations of computer vision while incorporating the latest deep learning advances. Taking a holistic approach that goes beyond the machine learning aspects, it addresses fundamental issues in the task of vision and the relationship of machine vision to human perception while cogently integrating concepts across disciplinary and historical bounds. Extensive illustrations, examples, and thought-provoking questions emphasize intuitive learning, while how-to sections tackle the research process and other pragmatic issues left out of standard texts. Written by leaders in the field and honed by a decade of classroom experience, this engaging and highly teachable book offers an essential next-generation view of computer vision. Up-to-date treatment integrates classic computer vision and deep learning Covers topics not standard in other texts, including signal processing, aliasing, statistical image models, issues of fairness and ethics, and the research process Accessible approach emphasizes fundamentals and assumes little background knowledge Student-friendly presentation features extensive examples and images Proven in the classroom Instructor resources include slides, solutions, and source code