Many methods for 3D reconstruction in computer vision rely on probability models, for example, Bayesian reasoning. Here we introduce a probability model of surface visibilities in ...
In this paper, we present an efficient algorithm for 3D object recognition in presence of clutter and occlusions in noisy, sparse and unsegmented range data. The method uses a robu...
This paper presents a novel probabilistic framework for 3D surface reconstruction from multiple stereo images. The method works on a discrete voxelized representation of the scene...
When an observer moves in a 3D static scene, the motion field depends on the depth of the visible objects and on the observer’s instantaneous translation and rotation. By compu...
In this paper we present a novel view point independent range image segmentation and recognition approach. We generate a library of 3D models off-line and represent each model wit...