Markov Random Field Modeling in Image Analysis
Computer science workbenchPublished 1 January 2001
Stan Z. Li
Citations1,542
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TL;DR
This detailed and thoroughly enhanced third edition presents a comprehensive study / reference to theories, methodologies and recent developments in solving computer vision problems based on MRFs, statistics and optimisation.
Abstract
Markov random field (MRF) theory provides a basis for modeling contextual constraints in visual processing and interpretation. It enables us to develop optimal vision algorithms systematically when us
Keywords
Computer Science
Advances in pattern recognitionParameter Estimation in Optimal Object Recognition
3 Citations2009Stan Z. Li
This chapter1 presents a novel theory of parameter estimation for optimization-based object recognition where the optimal solution is defined as the global minimum of an energy function.