Rotation constrained power factorization for structure from motion of nonrigid objects

  • Authors:

  • Guanghui Wang;Hung-Tat Tsui;Q.M. Jonathan Wu

  • Affiliations:

  • Department of Electrical and Computer Engineering, University of Windsor, 401 Sunset Ave., Windsor, Ontario, Canada N9B 3P4 and Department of Electronic Engineering, The Chinese University of Hong ...;Department of Electronic Engineering, The Chinese University of Hong Kong, Shatin, NT, Hong Kong;Department of Electrical and Computer Engineering, University of Windsor, 401 Sunset Ave., Windsor, Ontario, Canada N9B 3P4

  • Venue:
  • Pattern Recognition Letters
  • Year:
  • 2008

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Abstract

The paper addresses the problem of recovering 3D structure and motion of nonrigid objects from image sequences. We propose a rotation constrained power factorization (RCPF) algorithm that combines the orthonormality and the replicated block structure of the motion matrix directly into iterations. The algorithm overcomes some limitations of previous SVD-based methods and can work with missing data. Based on the shape bases of the batch-type factorization, we also propose a sequential factorization technique to recover the shape and motion of new frames conveniently. Extensive experiments show the effectiveness of the proposed algorithm.