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Books > Computing & IT > Applications of computing > Artificial intelligence > Computer vision

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Bayesian Modeling of Uncertainty in Low-Level Vision (Hardcover, 1989 ed.) Loot Price: R3,150
Discovery Miles 31 500
Bayesian Modeling of Uncertainty in Low-Level Vision (Hardcover, 1989 ed.): Richard Szeliski

Bayesian Modeling of Uncertainty in Low-Level Vision (Hardcover, 1989 ed.)

Richard Szeliski

Series: The Springer International Series in Engineering and Computer Science, 79

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Loot Price R3,150 Discovery Miles 31 500 | Repayment Terms: R295 pm x 12*

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Vision has to deal with uncertainty. The sensors are noisy, the prior knowledge is uncertain or inaccurate, and the problems of recovering scene information from images are often ill-posed or underconstrained. This research monograph, which is based on Richard Szeliski's Ph.D. dissertation at Carnegie Mellon University, presents a Bayesian model for representing and processing uncertainty in low level vision. Recently, probabilistic models have been proposed and used in vision. Sze liski's method has a few distinguishing features that make this monograph im portant and attractive. First, he presents a systematic Bayesian probabilistic estimation framework in which we can define and compute the prior model, the sensor model, and the posterior model. Second, his method represents and computes explicitly not only the best estimates but also the level of uncertainty of those estimates using second order statistics, i.e., the variance and covariance. Third, the algorithms developed are computationally tractable for dense fields, such as depth maps constructed from stereo or range finder data, rather than just sparse data sets. Finally, Szeliski demonstrates successful applications of the method to several real world problems, including the generation of fractal surfaces, motion estimation without correspondence using sparse range data, and incremental depth from motion."

General

Imprint: Springer
Country of origin: Netherlands
Series: The Springer International Series in Engineering and Computer Science, 79
Release date: September 1989
First published: 1989
Authors: Richard Szeliski
Dimensions: 235 x 155 x 14mm (L x W x T)
Format: Hardcover
Pages: 198
Edition: 1989 ed.
ISBN-13: 978-0-7923-9039-8
Categories: Books > Computing & IT > Applications of computing > Artificial intelligence > Computer vision
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LSN: 0-7923-9039-3
Barcode: 9780792390398

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