Nonparametric motion model

Motion information is a powerful cue for visual perception. In the context of video indexing and retrieval, motion content serves as a useful source for compact video representation. There has been a lot of literature about parametric motion models. However, it is hard to secure a proper parametric assumption in a wide range of video scenarios. Diverse camera shots and frequent occurrences of improper optical flow estimation or block matching motivate us to develop nonparametric motion models. In this demonstration, we present a novel nonparametric motion model. The unique features mainly include: 1) Instead of computationally expensive and vulnerable parametric regression our proposed model bases the motion characterization on the classification of motion patterns; 2) we employ machine learning to capture the knowledge of recognizing camera motion patterns from bad motion vector fields (MVF); and 3) with the mean shift filtering our proposed motion representation elegantly incorporat...

• Type: Conference
• Year: 2004
• Where: MM
• Authors: Ling-Yu Duan, Min Xu, Qi Tian, Changsheng Xu
• Keywords: Camera Motion, MM 2004, Motion Model, Nonparametric Motion