Two tightly coupled subproblems need to be solved for locating and recognizing the model: the correspondence problem (how are scene features put into correspondence with model features?),

Two tightly coupled subproblems need to be solved for locating and recognizing the model: the correspondence problem (how are scene features put into correspondence with model features?),

Chien-Ping Lu and Eric Mjolsness Department of Computer Science Yale University New Haven, CT 06520-8285 Abstract We present a Mean Field Theory method for locating twodimensional objectsthat have undergone rigid transformations. The resulting algorithm is a form of coarse-to-fine correlation matching. We first consider problems of matching synthetic point data, and derive a point matching objective function. A tractable line segment matching objective function is derived by considering each line segment as a dense collection of points, and approximating itby a sum of Gaussians. The algorithm is tested on real images from which line segments are extracted and matched. 1 Introduction Assume that an object in a scene can be viewed as an instance of the model placed in space by some spatial transformation, and object recognition is achieved by discovering aninstance of the model in the scene.