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This paper proposes an accuracy-distortion model for overcomplete wavelet-based scalable motion estimation by exploiting the theory of stationary random process. We first estimate the motion compensation errors in spatial domain due to inaccurate motion vectors, then extend the results to overcomplete wavelet domain, and further derive the errors caused by fraction-pixel motion vectors. Finally, combining with a visibility model of wavelet coefficient errors, this paper proposes a novel algorithm to estimate the motion vector accuracy with which the motion compensation errors will be invisible. Experimental results show that the proposed algorithm is effective in estimating the visually lossless accuracy threshold of motion vectors. The proposed algorithm can be used in scalable coding of motion vectors. Also it can accelerate the motion estimation speed by stopping halfway at the accuracy that will not cause any visible errors.