Motion Vector Smoothing for True Motion Estimation

Hai Bing Yin, Xiangzhong Fang, Hua Yang, Songyu Yu, Xiaokang Yang

Abstract: This paper proposes a new motion vector (MV) smoothing algorithm to track the real motion in image sequences for MPEG video encoders. First, a pre-checking algorithm is employed to eliminate wrong motion vectors and preserve all possible motion vectors. For each block considered, the motion similarity between the neighboring blocks and the number of candidate motion vectors are jointly exploited to adaptively grow the filtering support, which is supposed to have homogeneous motion and sufficient spatial gradient. Then, all candidate motion vectors are checked within the filtering support using a new motion smoothness-constrained matching criteria. The simulation results show that the proposed algorithm can efficiently track the real motion resulting in smooth motion vector field (MVF).