Fields of Markov (MRF) the theory provides a base for the modeling of the contextual constraints in the visual treatment and l' interpretation. It allows a systematic development of the algorithms of vision optimal lorsqu' it is used with the principles d' optimization. This detailed work and carefully reinforced third edition presents a thorough study/reference to recent theories, methodologies and developments in the resolution of the problems of vision per computer based on recovery of the matters, of the statistics and d' optimization. It deals with the various problems from weak and the high level vision of calculation d' a manner systematic and unified within MAP-MRF-tallies. Among the tackled main questions are the following ones: how to use recovery of the matters for encoder the contextual constraints which are essential to the comprehension of l' image; how to derive the function objective for the optimal solution with a problem, and how to design data-processing algorithms to find a solution optimal. Easy to follow and coherent, l' revised edition is accessible, includes/understands the most recent projections, and has news and widened sections on subjects such as: Conditional Random Fields; for discrimination of random fields; Total Variation (TV) Model; space-time models, MRF and Bayesian Network (Graphical Models); propagation of belief; Graph Cuts and of detection of the faces and the recognition. Characteristics: • L' puts; accent on l' application of fields of Markov to problems of vision per computer, such as the restoration d' images and of detection of point in the field of low level, and l' object of l' pairing and recognition in the high level field • Introduce the readers to the basic concepts, the models d' important and various special categories of recovery of the matters on the network regular image, and recovery of the matters on the graphs relational to leave d' images • various models of vision present, within a unified framework, including the restoration and rebuilding d' images, EDGE and segmentation by area, texture, stereophony and the movement, corresponding object and of recognition and estimate of the installation • Use a d' variety; examples to illustrate the way of converting an implying specific problem of vision of uncertainties and the constraints into primarily a problem d' optimization under parameter MRF • Studies of discontinuities, an important matter in l' application of recovery of the matters to l' d' analyzes; image • Examine the problems d' estimate of the parameters of the model and l' optimization of functions within the framework of l' analyzes of texture and recognition d' objects • An exhaustive list of references includes/understands This vast scale and total volume is an excellent reference for the researchers who work in the vision by computer, d' treatment; images, recognition of the statistical models and the applications of recovery of the matters. It is also appropriate like a text for the advanced courses relative to these fields.

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