Object Localization Based on Mutual Information in Global Structure Constraint Model

In this paper, a kind of object representation model global structure constraint is presented, in which objects are described as constellations of points satisfied with their intrinsic specific global structure constraints. The spatial relations among all the patches of small color variations are extracted as shape model and the representative color information of patches are encoded and clustered as color model with color cluster information. Then, in the searching phase, mutual information is used as measurement with optimal algorithm to locate target objects in images by finding out the exactly matched position. In the experiment, we tested the approach on a collection of human face images and the results demonstrated the approach is simple, effective and efficient.