Effective camera motion analysis approach

Camera motion analysis (CMA) is very useful for many video content analysis tasks, but few works competently handle the videos with significant camera or object motion. In this paper, we present an effective CMA approach for such challenging cases. The effectiveness of our approach comes from two aspects: (1) reliably matching keypoints on consecutively sampled frames, where both the appearance similarity and motion smoothness of keypoints are considered; (2) effectively distinguishing background keypoints from foreground ones by a novel and advanced voting process, where the voting weights of keypoints are dynamically adjusted to guarantee that the influence of foreground motion can be largely reduced in CMA. Thus, a parametric camera motion model can be naturally derived by the accurate estimation of the motion of background keypoints. The experimental results on the TRECV2005 dataset and 500 shots from seven classic action movies demonstrate the effectiveness of our approach.