A self-adaptive weighted affinity propagation clustering for key frames extraction on human action recognition

作者：Wang Yongxiong^*; Sun Shuxin; Ding Xueming

来源：Journal of Visual Communication and Image Representation, 2015, 33: 193-202.

DOI：10.1016/j.jvcir.2015.09.013

• Key frames extraction
• 3D video sequences
• Energy feature
• Kinetic energy
• Potential energy
• Self-adaptive weighted AP clustering
• SVM
• Human activity recognition

In this paper, we propose a novel approach for key frames extraction on human action recognition from 3D video sequences. To represent human actions, an Energy Feature (EF), combining kinetic energy and potential energy, is extracted from 3D video sequences. A Self-adaptive Weighted Affinity Propagation (SWAP) algorithm is then proposed to extract the key frames. Finally, we employ SVM to recognize human actions on the EFs of selected key frames. The experiments show the information including whole action course can be effectively extracted by our method, and we obtain good recognition performance without losing classification accuracy. Moreover, the recognition speed is greatly improved.

• 出版日期2015-11
• 单位上海理工大学