Bayesian Modeling of Uncertainty in Low-Level Vision.pdf

Bayesian Modeling of Uncertainty in Low-Level Vision PDF

Richard Szeliski

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 Szeliskis 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 liskis 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.

The Night Fire . Michael Connelly . 9.18 € 10.80 € Bayesian Modeling of Uncertainty in Low-Level …

5.39 MB DATEIGRÖSSE
1461289041 ISBN
Englisch SPRACHE
Bayesian Modeling of Uncertainty in Low-Level Vision.pdf

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Pris: 1679 kr. Häftad, 2011. Skickas inom 5-8 vardagar. Köp Bayesian Modeling of Uncertainty in Low-Level Vision av Richard Szeliski på Bokus.com. Bayesian Modeling of Uncertainty in Low-Level Vision ebook ...

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Jessica Kohmann

30.09.1989 · Bayesian Modeling of Uncertainty in Low-Level Vision book. Read reviews from world’s largest community for readers. Vision has to deal with uncertainty.