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. © 2012 Springer-Verlag.
CITATION STYLE
Ballester, C., Garrido, L., Lazcano, V., & Caselles, V. (2012). A TV-L1 optical flow method with occlusion detection. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7476 LNCS, pp. 31–40). https://doi.org/10.1007/978-3-642-32717-9_4
Mendeley helps you to discover research relevant for your work.