Spatial and Fourier Error Minimization for Motion Estimation and Segmentation

  • Authors:
  • Alexia Briassouli;Narendra Ahuja

  • Affiliations:
  • University of Illinois at Urbana-Champaign;University of Illinois at Urbana-Champaign

  • Venue:
  • ICPR '06 Proceedings of the 18th International Conference on Pattern Recognition - Volume 01
  • Year:
  • 2006

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Abstract

We present a new approach to motion estimation by minimizing the squared error in both the spatial and frequency domains and we show that the spatially global nature of FT leads to a motion estimation error that is much lower than that obtained via spatial motion estimation. On the other hand, spatial analysis is useful for accurate segmentation. We describe a novel, hybrid approach combining the above two estimates of motion and segmentation. We examine the robustness of minimizing the error terms in both domains, both theoretically and experimentally. Experiments with real and synthetic sequences demonstrate the capabilities of the proposed algorithm.