Title :
Aggressive motion detection based on normalised Radon transform and online AdaBoost
Author :
Jia, Chungang ; Lu, Hai-Han ; Zhang, Rongting
Author_Institution :
Dept. of Electron. Eng., Dalian Univ. of Technol., Dalian
Abstract :
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.
Keywords :
Radon transforms; edge detection; estimation theory; feature extraction; image classification; image motion analysis; image sequences; learning (artificial intelligence); matrix algebra; microprocessor chips; aggressive motion detection; background subtraction; binary rectangle; connected chip linking; contour information extraction; feature selection classifier; image sequence; mean-shift estimation; normalised Radon matrix transform; online AdaBoost; stationary camera;
Journal_Title :
Electronics Letters
DOI :
10.1049/el:20092891
