Abstract
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.
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Kato, T., Itoh, H., Imiya, A. (2015). Optical Flow Computation with Locally Quadratic Assumption. In: Azzopardi, G., Petkov, N. (eds) Computer Analysis of Images and Patterns. CAIP 2015. Lecture Notes in Computer Science(), vol 9256. Springer, Cham. https://doi.org/10.1007/978-3-319-23192-1_19
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DOI: https://doi.org/10.1007/978-3-319-23192-1_19
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