A Comprehensive Evaluation on Non-deterministic Motion Estimation

Abstract

When computing optical flow with region-based matching, very few of them can be reliably obtained, especially for the high-contrast areas or those with little texture. Instead of using a single pixel from the reference frame, non-deterministic motion utilizes multiple pixels within a neighborhood to represent the corresponding pixel in the current frame. Although remarkable improvement has been made with this method, the weight associated to each reference pixel is quite sensitive to the selection of its standard deviation. To address this issue, a dual probability is presented in this paper. Intuitively, it enhances those weights of pixels that are more similar to its counterpart in the current frame, while suppressing the rest of them. Experimental results show that the proposed method is effective to deal with intense motion and occlusion, especially in the case of reducing the adverse impact of noise.