Abstract
Usually, optical flow computation is based on grayscale images and the brightness conservation assumption. Recently, some authors have investigated in transferring gradient-based grayscale optical flow methods to color images. These color optical flow methods are restricted to brightness and color conservation over time. In this paper, a correlation-based color optical flow method is presented that allows for brightness and color changes within an image sequence. Further on, the correlation results are used for a probabilistic evaluation that combines the velocity information gained from single color frames to a joint velocity estimate including all color frames. The resulting color optical flow is compared to other representative multi-frame color methods and standard single-frame grayscale methods.
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Willert, V., Eggert, J., Clever, S., Körner, E. (2005). Probabilistic Color Optical Flow. In: Kropatsch, W.G., Sablatnig, R., Hanbury, A. (eds) Pattern Recognition. DAGM 2005. Lecture Notes in Computer Science, vol 3663. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11550518_2
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DOI: https://doi.org/10.1007/11550518_2
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