Graphical models for inference and learning in computer vision
Graphical models are indispensable as tools for inference in computer vision, where highly structured and interdependent output spaces can be described in terms of low-order, local relationships. One such problem is that of graph matching, where the goal is to localise various parts of an object within an image: although the number of joint configurations of these parts may be very large, the relationships between them can typically be described in terms of simple skeletal structures, which...[Show more]
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