Abstract
Motion estimation is a key problem in the analysis of image sequences. From a sequence of images we can only estimate an approximation of the image motion field called optical flow. We propose to improve optical flow estimation by including information from images of textural features. We compute the optical flow from intensity and textural images from first-order derivatives, then combine estimates using the spatial gradient as confidence measure. Experimental results with images for which the ground-truth optical flow is known show clearly that the estimate improves by including estimates from textural images. Experiments with several underwater images also show a qualitative improvement.
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