This paper introduces a uniform statistical framework for both 3-D and 2-D object recognition using intensity images as input data. The theoretical part provides a mathematical too...
We present a method to learn and recognize object class models from unlabeled and unsegmented cluttered scenes in a scale invariant manner. Objects are modeled as flexible constel...
Abstract. In this paper, we deal with the problem of partially observed objects. These objects are defined by a set of points and their shape variations are represented by a statis...
In this paper, we describe a new design of a recognition system for a single image of indoor scene including complex occlusions. In our system, rst, the system estimates 3D struc...
In this contribution we introduce the Multiocular Contracting Curve Density algorithm (MOCCD), a novel method for fitting a 3D parametric curve. The MOCCD is integrated into a tr...