Efficiency Analysis of POC-Derived Bases for Combinatorial Motion Estimation
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.
KeywordsGround Truth Motion Vector Motion Estimation Block Match Reduction Stage
- 9.Veksler, O.: Reducing search space for stereo correspondence with graph cuts. In: British Machine Vision Conference, vol. 2, pp. 709–719 (2006)Google Scholar
- 10.Alba, A., Arce-Santana, E., Aguilar Ponce, R.M., Campos-Delgado, D.U.: Phase-correlation guided area matching for realtime vision and video encoding. Journal of Real-Time Image Processing (2012) (in press)Google Scholar