Applications of Stochastic Geometry in Image Analysis
A discussion is given of various stochastic geometry models (random fields, sequential object processes, polygonal field models) which can be used in intermediate‐ and high‐level image analysis. Two examples are presented of actual image analysis problems (motion tracking in video, foreground/background separation) to which these ideas can be applied.
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