A Novel Trajectory Clustering Approach for Motion Segmentation

We propose a novel clustering scheme for spatio-temporal segmentation of sparse motion fields obtained from feature tracking. The approach allows for the segmentation of meaningful motion components in a scene, such as shortand long-term motion of single objects, groups of objects and camera motion. The method has been developed within a project on the analysis of low-quality archive films. We qualitatively and quantitatively evaluate the performance and the robustness of the approach. Results show, that our method successfully segments the motion components even in particularly noisy sequences.