Motion Segmentation in the Presence of Outlying, Incomplete, or Corrupted Trajectories

—In this paper, we study the problem of segmenting tracked feature point trajectories of multiple moving objects in an image sequence. Using the affine camera model, this problem can be cast as the problem of segmenting samples drawn from multiple linear subspaces. In practice, due to limitations of the tracker, occlusions, and the presence of nonrigid objects in the scene, the obtained motion trajectories may contain grossly mistracked features, missing entries, or corrupted entries. In this paper, we develop a robust subspace separation scheme that deals with these practical issues in a unified mathematical framework. Our methods draw strong connections between lossy compression, rank minimization, and sparse representation. We test our methods extensively on the Hopkins155 motion segmentation database and other motion sequences with outliers and missing data. We compare the performance of our methods to state-of-the-art motion segmentation methods based on expectation-maximizati...

• Type: Journal
• Year: 2010
• Where: PAMI
• Authors: Shankar Rao, Roberto Tron, René Vidal, Yi Ma
• Keywords: Feature Point Trajectories, Motion Segmentation, Obtained Motion Trajectories, PAMI 2010