Efficiency Analysis of POC-Derived Bases for Combinatorial Motion Estimation

  • Alejandro Reyes
  • Alfonso Alba
  • Edgar Arce-Santana
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8333)


Motion estimation is a fundamental problem in many computer vision applications. One solution to this problem consists in defining a large enough set of candidate motion vectors, and using a combinatorial optimization algorithm to find, for each point of interest, the candidate which best represents the motion at the point of interest. The choice of the candidate set has a direct impact in the accuracy and computational complexity of the optimization method. In this work, we show that a set containing the most representative maxima of the phase-correlation function between the two input images, computed for different overlapping regions, provides better accuracy and contains less spurious candidates than other choices in the literature. Moreover, a pre-selection stage, based in a local motion estimation algorithm, can be used to further reduce the cardinality of the candidate set, without affecting the accuracy of the results.


Ground Truth Motion Vector Motion Estimation Block Match Reduction Stage 
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 2014

Authors and Affiliations

  • Alejandro Reyes
    • 1
  • Alfonso Alba
    • 1
  • Edgar Arce-Santana
    • 1
  1. 1.Facultad de CienciasUniversidad Autónoma de San Luis PotosíSan Luis PotosíMéxico

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