Robust object pose estimation from feature-based stereo

This paper addresses the problem of computing the three-dimensional (3-D) path of a moving rigid object using a calibrated stereoscopic vision setup. The proposed system begins by detecting feature points on the moving object. By tracking these points over time, it produces clouds of 3-D points that can be registered, thus giving information about the underlying camera motion. A novel correction scheme that compensates for the accumulated error in the computed positions by automatic detection of loop-back points in the movement of the object is also proposed. An application to object modeling is presented in which a handheld object is moved in front of a camera and is reconstructed using silhouette intersection.