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Robust motion estimation using spatial Gabor-like filters
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DOI：10.1016/S0165-1684(01)00188-8.png)
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This paper presents a new algorithm for motion estimation. It combines Gabor-like filter decomposition and robust least-squares estimation in a multiresolution framework. The spatial Gabor-like filter bank, based on recursive implementation, provides a fast multichannel decomposition of frame sequence. Then, applying the brightness Constancy constraint on each channel between two consecutive frames, an over-determined system of velocity equations at each pixel is obtained, In order to be robust to outliers, this over-determined system is solved using a robust least-squares technique. A multiresolution framework is used in order to manage large and small displacements. Two kinds of recursive filter implementation have been tested: whereas third order filtering is very similar to a real Gabor filter, first order recursive filters are fastest and can be implemented with very large scale integration (VLSI) analog circuit. Performances of our algorithm for the two filter implementations are tested on synthetic and real sequences, and are compared with other techniques. (C) 2002 Elsevier Science B.V. All rights reserved.
Keyword:
motion estimation
Gabor filter bank
recursive filters
robust least-squares
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