Learning multiscale image models of 2D object classes

摘要

This paper is concenred with learning the canonical gray scale structure of the images of a class of objects. Structure is defined in terms of the geometry and layout of salient image regions that characterize the given views of the objects. The use of such structure based learning of object appearence is movtivated by the relative stability of image structure over intensity values. A multiscale ssegmentation tree description is automatically rextranced for all sample image which are then matched to construct a single canonical representative which serves as the model of the class.