Optic flow estimation using the Hermite transform

In this paper we present a spatiotemporal energy based method to estimate motion from an image sequence. A directional energy is defined in terms of the Radon projections of the Hermite transform. Radon transform provides a suitable representation for image orientation analysis, while Hermite transform describes image features locally in term of Gaussian derivatives. These operators have been used in computer vision for feature extraction and are relevant in visual system modeling. A directional response defined from the directional energy is used to estimate local motion as well as to compute a confidence matrix. This matrix provides a confidence measure for our estimate and is used to propagate the velocity information towards directions with high uncertainty. With this results, there can be applications ranging from motion compensation, and tracking of moving objects, to segmentation and video compression.

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