Incorporating Non-motion Cues into 3D Motion Segmentation

We address the problem of segmenting an image sequence into rigidly moving 3D objects. An elegant solution to this problem is the multibody factorization approach in which the measurement matrix is factored into lower rank matrices. Despite progress in factorization algorithms, the performance is still far from satisfactory and in scenes with missing data and noise, most existing algorithms fail. In this paper we propose a method for incorporating 2D non-motion cues (such as spatial coherence) into multibody factorization. We formulate the problem in terms of constrained factor analysis and use the EM algorithm to find the segmentation. We show that adding these cues improves performance in real and synthetic sequences.

• Type: Conference
• Year: 2006
• Where: ECCV
• Authors: Amit Gruber, Yair Weiss
• Keywords: 2D Non-motion Cues, Computer Vision, Constrained Factor Analysis, Cues Improves Performance, ECCV 2006, Lower Rank Matrices, Multibody Factorization Approach