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 Richard Szeliski - Springer
The book emphasizes basic techniques that work under real-world conditions, not the esoteric mathematics without practical applicability. The text is suitable for a senior-level undergraduates in computer science and electrical engineering.
by Aapo Hyvarinen, Jarmo Hurri, Patrik O. Hoyer - Springer
Introductory textbook and a research monograph on modelling the statistical structure of natural images. The statistical structure of natural images is described using a number of statistical models whose parameters are estimated from image samples.
by S. Dance, Z.Q. Liu, T.M. Caelli - World Scientific
Explores a method for symbolically intrepreting images based upon a parallel implementation of a network-of-frames to describe intelligent processing. The system has been implemented in an object-oriented environment in the language Parlog++.
by Jean Gallier - arXiv
These are notes on the method of normalized graph cuts and its applications to graph clustering. I provide a thorough treatment of this deeply original method, including complete proofs. The main thrust of this paper is the method of normalized cuts.