[PDF.46bq] Bayesian Modeling of Uncertainty in Low-Level Vision (The Springer International Series in Engineering and Computer Science)

Bayesian Modeling of Uncertainty in Low-Level Vision (The Springer International Series in Engineering and Computer Science)

[PDF.xx94] Bayesian Modeling of Uncertainty in Low-Level Vision (The Springer International Series in Engineering and Computer Science)

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 | #7099668 in Books |  Springer |  1989-09-30 | Original language:English | PDF # 1 |  9.21 x.56 x6.14l,1.07 | File type: PDF | 198 pages

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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 use...

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