Stochastic Algorithms for Visual Tracking - Probabilistic Modelling and Stochastic Algorithms for Visual Localisation and Tracking (Paperback, Softcover reprint of the original 1st ed. 2002)

A central problem in computer vision is to track objects as they move and deform in a video sequence. Stochastic algorithms -- in particular, particle filters and the Condensation algorithm -- have dramatically enhanced the state of the art for such visual tracking problems in recent years. This book presents a unified framework for visual tracking using particle filters, including the new technique of partitioned sampling which can alleviate the "curse of dimensionality" suffered by standard particle filters. The book also introduces the notion of contour likelihood: a collection of models for assessing object shape, colour and motion, which are derived from the statistical properties of image features. Because of their statistical nature, contour likelihoods are ideal for use in stochastic algorithms. A unifying theme of the book is the use of statistics and probability, which enable the final output of the algorithms presented to be interpreted as the computer's "belief" about the state of the world. The book will be of use and interest to students, researchers and practitioners in computer vision, and assumes only an elementary knowledge of probability theory.

General

Imprint:	Springer London
Country of origin:	United Kingdom
Series:	Distinguished Dissertations
Release date:	September 2011
First published:	2002
Authors:	John MacCormick
Dimensions:	235 x 155 x 10mm (L x W x T)
Format:	Paperback
Pages:	174
Edition:	Softcover reprint of the original 1st ed. 2002
ISBN-13:	978-1-4471-1176-4
Categories:	Books > Computing & IT > General theory of computing > Data structures Books > Computing & IT > Computer programming > Algorithms & procedures Books > Computing & IT > Applications of computing > Artificial intelligence > Computer vision
LSN:	1-4471-1176-1
Barcode:	9781447111764

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