Hierarchical model-based motion estimation

  • James R. Bergen
  • P. Anandan
  • Keith J. Hanna
  • Rajesh Hingorani
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 588)


This paper describes a hierarchical estimation framework for the computation of diverse representations of motion information. The key features of the resulting framework (or family of algorithms) are a global model that constrains the overall structure of the motion estimated, a local model that is used in the estimation process, and a coarse-fine refinement strategy. Four specific motion models: affine flow, planar surface flow, rigid body motion, and general optical flow, are described along with their application to specific examples.


Flow Field Optical Flow Local Model Motion Estimation Motion Model 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 1992

Authors and Affiliations

  • James R. Bergen
    • 1
  • P. Anandan
    • 1
  • Keith J. Hanna
    • 1
  • Rajesh Hingorani
    • 1
  1. 1.David Sarnoff Research CenterPrincetonUSA

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