Evaluation and selection of models for motion segmentation

Abstract

We first present an improvement of the subspace separation for motion segmentation by newly introducing the affine space constraint. We point out that this improvement does not always fare well due to the effective noise it introduces. In order to judge which solution to adopt if different segmentations are obtained, we test two measures using real images: the standard F test, and the geometric model selection criteria.