Efficiency analysis of POC-derived bases for combinatorial motion estimation Conference Paper uri icon


  • 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. © 2014 Springer-Verlag Berlin Heidelberg.

publication date

  • 2014-01-01