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Aggressive motion detection based on normalised Radon transform and online AdaBoost

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3 Author(s)
Jia, C. ; Dept. of Electron. Eng., Dalian Univ. of Technol., Dalian ; Lu, H. ; Zhang, R.

A framework for human aggressive motion detection in image sequences captured from a single stationary camera is described. Background subtraction, connected chips linking and mean-shift estimation are used to extract target contour information. The binary rectangle containing contour points of the blob-set is transformed into a normalised Radon matrix. With labelled (normal or aggressive motion) Radon matrix as feature pools an online AdaBoost feature selection is implemented. Using the selected classifiers the human aggressive motion in a frame can be recognised. Experimental results show that the system performs well.

Published in:

Electronics Letters  (Volume:45 ,  Issue: 5 )