Finding Planes and Clusters of Objects from 3D Line Segments with Application to 3D Motion Determination

Abstract

We address in this paper how to find clusters based on proximity and planar facets based on coplanarity from 3D line segments obtained from stereo. The proposed methods are efficient and have been tested with many real stereo data. These procedures are indispensable in many applications including scene interpretation, object modeling, and object recognition. We show their application to 3D motion determination. We have developed an algorithm based on the hypothesize-and-verify paradigm to register two consecutive 3D frames obtained from stereo and estimate their transformation/motion. By grouping 3D line segments in each frame into clusters and planes, we can reduce effectively the complexity of the hypothesis generation phase.