Scene labeling: an optimization approach

摘要

This paper deals with an optimization technique applied to the problem of stochastic labeling. We propose a definition of a global criterion on a set of objects to be labeled that combines both ambiguity and consistency with adjustable weights. A projected gradient algorithm is developed to minimize the criterion. Results are shown on a toy example and on the edge detection problem. Comparisons are made with relaxation labeling techniques.