Photometric subspace for multibody motion segmentation

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This paper presents a new method for automatically separating the motion of multiple independently moving objects in a sequence of images based on the notion of photometric subspace. We show that intensities of observed trajectories of image features on a single body lie on a linearly independent frame space with three, or fewer, dimensions. We then argue that it is possible in theory to determine the grouping of the feature points by way of separating the photometric subspaces. As a clue for practical separation, we also introduce the surface interaction matrix which is valid for Lambertian reflectance surface. Recently, several authors have presented different algorithms on this task of grouping by factorization-based procedures using the coordinates of image features. While the challenges in their approaches are to realize the robust performance in the presence of noise, we propose to incorporate the above photometric analysis available at given feature points in the conventional schemes of motion segmentation, and show that the performance is indeed stabilized through experiments on real and synthetic image sequences

论文关键词:Subspace separation,Motion segmentation,Physics-based vision

论文评审过程:Received 21 August 2002, Revised 23 January 2004, Accepted 28 January 2004, Available online 9 April 2004.

论文官网地址:https://doi.org/10.1016/j.imavis.2004.01.004