by Dana H. Ballard, Christopher M. Brown
Publisher: Prentice Hall 1982
Number of pages: 539
Computer vision is the construction of explicit, meaningful descriptions of physical objects from images. Image understanding is very different from image processing, which studies image-to-image transformations, not explicit description building. Descriptions are a prerequisite for recognizing, manipulating, and thinking about objects. Parts of the book assume some mathematical and computing background (calculus, linear algebra, data structures, numerical methods). However, throughout the book mathematical rigor takes a backseat to concepts. Our intent is to transmit a set of ideas about a new field to the widest possible audience.
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Nearest feature classification for face recognition, subspace methods, a multi-stage classifier for face recognition undertaken by coarse-to-fine strategy, PCA-ANN face recognition system based on photometric normalization techniques, etc.
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This book is about visual perception. It is based on the author's experience in teaching graduate courses in the field. It assumes no previous knowledge of the field and aims to provide a comprehensive knowledge of its methods.
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