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      • Department of Electrical and Electronics Engineering
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      Gibbs random field model based 3-D motion estimation from video sequences

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      Author(s)
      Alatan, A. A.
      Levent, O.
      Date
      1994
      Source Title
      Proceedings of SPIE - The International Society for Optical Engineering
      Print ISSN
      0277-786X
      Publisher
      IEEE
      Volume
      2308
      Pages
      626 - 637
      Language
      English
      Type
      Article
      Item Usage Stats
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      Abstract
      In contrast to previous global 3D motion concept, a Gibbs random field based method, which models local interactions between motion parameters defined at each point on the object, is proposed. An energy function which gives the joint probability distribution of motion vectors, is constructed. The energy function is minimized in order to find the most likely motion vector set. Some convergence problems, due to ill-posedness of the problem, are overcome by using the concept of hierarchical rigidity. In hierarchical rigidity, the objects are assumed to be almost rigid in the coarsest level and this rigidness is weakened at each level until the finest level is reached. The propagation of motion information between levels, is encouraged. At the finest level, each point have a motion vector associated with it and the interaction between these vectors are described by the energy function. The minimization of the energy function is achieved by using hierarchical rigidity, without trapping into a local minimum. The results are promising.
      Keywords
      Gibbs random field
      Motion estimation
      Three dimensional motion
      Computer vision
      Probability
      Three dimensional
      Video signal processing
      Image processing
      Permalink
      http://hdl.handle.net/11693/25942
      Published Version (Please cite this version)
      http://doi.org/10.1109/ICIP.1994.413679
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      • Department of Electrical and Electronics Engineering 4012
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