The purpose of this paper is twofold. First, we develop a quadratic tracker which computes a locally quadratic optical flow field by solving a model-fitting problem for each point in its local neighbourhood. This local method allows us to select a region of interest for the optical flow computation. Secondly, we propose a method to compute the transportation of a motion field in long-time image sequences using the Wasserstein distance for cyclic distributions. This measure evaluates the motion coherency in an image sequence and detects collapses of smoothness of the motion vector field in an image sequence.
CITATION STYLE
Kato, T., Itoh, H., & Imiya, A. (2015). Optical flow computation with locally quadratic assumption. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9256, pp. 223–234). Springer Verlag. https://doi.org/10.1007/978-3-319-23192-1_19
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