Motion analysis is still a challenging task in many computer vision applications. This paper proposes a new low-level motion feature based on geometric regularity information, particularly suited for traffic surveillance. Firstly, a novel concept of temporal geometry consistency constraint (TGCC) is introduced, which exploits the fact that the geometric structure of a rigid object remains consistent across consecutive frames. Furthermore, the spatial geometric flow is adopted to characterize image structure. Finally, the video motion is represented as a set of geometric flow that moves in the temporal direction. In this case, the method yields a promising illumination robust moderately dense geometric motion flow (GMF) and has more explicit motion boundaries. The GMF could also be used for higher level motion modeling and structural inference tasks, as an effective low-level feature. Extensive experiment results on real video demonstrate the effectiveness and robustness of the proposed method for vehicle motion analysis.
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