Optical flow and total least squares solution for multi-scale data in an over-determined system
ISVC'07 Proceedings of the 3rd international conference on Advances in visual computing - Volume Part II
A study of the yosemite sequence used as a test sequence for estimation of optical flow
SCIA'05 Proceedings of the 14th Scandinavian conference on Image Analysis
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A new algorithm for accurate optical flow (OF) estimation using discrete wavelet approximation is proposed. The computation of OF depends on minimizing the image and smoothness constraints. The proposed method takes advantages of the nature of wavelet theory, which can efficiently and accurately approximate any function. OF vectors and image functions are represented by means of linear combinations of scaling basis functions. Based on such wavelet-based approximation, the leading coefficients of these basis functions carry global information about the approximated functions. The proposed method can successfully convert the problem of minimizing a constraint function into that of solving a linear system of a quadratic and convex function of scaling coefficients. Once all the corresponding coefficients are determined, the flow vectors can be obtained accordingly. Experiments have been conducted on both synthetic and real image sequences. In terms of accuracy, the results show that our approach outperforms the existing methods which adopted the same objective function as ours