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This paper focuses on human action recognition in video sequences. A method based on the optical flow estimation is presented, where critical points of the flow field are extracted. Multi-scale trajectories are generated from those points and are characterized in the frequency domain. Finally, a sequence is described by fusing this frequency information with motion orientation and shape information. Experiments show that this method has recognition rates among the highest in the state of thedoi:10.1109/icip.2014.7025289 dblp:conf/icip/BeaudryPM14 fatcat:2lmenanrvnhprdsfeqzcwnhgi4