In this paper we present an approach to speed up the computation of sparse optical flow fields by means of integral images and provide implementation details. Proposing a modification of the Lucas-Kanade energy functional allows us to use integral images and thus to speed up the method notably while affecting only slightly the quality of the computed optical flow. The approach is combined with an efficient scanline algorithm to reduce the computation of integral images to those areas where there are features to be tracked. The proposed method can speed up current surveillance algorithms used for scene description and crowd analysis. © 2010 Springer-Verlag.
CITATION STYLE
Senst, T., Eiselein, V., & Sikora, T. (2010). II-LK - A real-time implementation for sparse optical flow. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 6111 LNCS, pp. 240–249). https://doi.org/10.1007/978-3-642-13772-3_25
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