A Stochastic Grammar of Images (Foundations and Trends free

Author: Song-Chun Zhu
Edition:
Publisher: Now Publishers Inc
Binding: Paperback
ISBN: 1601980604
Category: Programming
List Price: $ 80.00
Price: $ 68.23
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A Stochastic Grammar of Images (Foundations and Trends(r) in Computer Graphics and Vision)

A Stochastic Grammar of Images is the first book to provide a foundational review and perspective of grammatical approaches to computer vision. Programming books A Stochastic Grammar of Images (Foundations and Trends pdf. In its quest for a stochastic and context sensitive grammar of images, it is intended to serve as a unified frame-work of representation, learning, and recognition for a large number of object categories. It starts out by addressing the historic trends in the area and overviewing the main concepts: such as the and-or graph, the parse graph, the dictionary and goes on to learning issues, semantic gaps between symbols and pixels, dataset for learning and algorithms. The proposal grammar presented integrates three prominent representations in the literature: stochastic grammars for composition, Markov (or graphical) models for contexts, and sparse coding with primitives (wavelets). It also combines the structure-based and appearance based methods in the vision literature. Download books pdf via mediafire, 4shared, rapidshare.

Download A Stochastic Grammar of Images (Foundations and Trends

In its quest for a stochastic and context sensitive grammar of images, it is intended to serve as a unified frame-work of representation, learning, and recognition for a large number of object categories. It starts out by addressing the historic trends in the area and overviewing the main concepts: such as the and-or graph, the parse graph, the dictionary and goes on to learning issues, semantic gaps between symbols and pixels, dataset for learning and algorithms. The proposal grammar presented integrates three prominent representations in the literature: stochastic grammars for composition, Markov (or graphical) models for contexts, and sparse coding with primitives (wavelets). It also combines the structure-based and appearance based methods in the vision literature. At the end of the review, three case studies are presented to illustrate the proposed grammar. A Stochastic Grammar of Images is an important contribution to the literature on structured statistical models in computer vision. Download free A Stochastic Grammar of Images (Foundations and Trends(r) in Computer Graphics and Vision) pdf