Abstract
In this paper we propose a variational model for joint optical flow and occlusion estimation. Our work stems from the optical flow method based on a TV-L 1 approach and incorporates information that allows to detect occlusions. This information is based on the divergence of the flow and the proposed energy favors the location of occlusions on regions where this divergence is negative. Assuming that occluded pixels are visible in the previous frame, the optical flow on non-occluded pixels is forward estimated whereas is backwards estimated on the occluded ones. We display some experiments showing that the proposed model is able to properly estimate both the optical flow and the occluded regions.
Keywords
- Optical Flow
- Consecutive Frame
- Occlude Region
- Intensity Match
- Occlusion Area
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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Ballester, C., Garrido, L., Lazcano, V., Caselles, V. (2012). A TV-L1 Optical Flow Method with Occlusion Detection. In: Pinz, A., Pock, T., Bischof, H., Leberl, F. (eds) Pattern Recognition. DAGM/OAGM 2012. Lecture Notes in Computer Science, vol 7476. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32717-9_4
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DOI: https://doi.org/10.1007/978-3-642-32717-9_4
Publisher Name: Springer, Berlin, Heidelberg
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