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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by Widodo Budiharto - Science Publishing Group
This book is written to provide an introduction to intelligent robotics using OpenCV. It is intended for a first course in robot vision and covers modeling and implementation of intelligent robot. Written for student and hobbyist.
by Peng-Yeng Yin - IN-TECH
The present book is intended to collect representative researches around the globe focusing on low-level vision, filter design, features and image descriptors, data mining and analysis, and biologically inspired algorithms.
by Andrew Blake, Andrew Zisserman - The MIT Press
Visual Reconstruction presents a unified and highly original approach to the treatment of continuity in vision. The book introduces two new concepts: the weak continuity constraint and the graduated nonconvexity algorithm.
by Julio Ponce, Adem Karahoca - IN-TECH
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.