Articulated motion reconstruction from feature points
Pattern Recognition
Measurement of Pedestrian Groups Using Subtraction Stereo
ISVC '09 Proceedings of the 5th International Symposium on Advances in Visual Computing: Part II
Multi-posture human detection in video frames by motion contour matching
ACCV'07 Proceedings of the 8th Asian conference on Computer vision - Volume Part I
Person authentication using 3D human motion
J-HGBU '11 Proceedings of the 2011 joint ACM workshop on Human gesture and behavior understanding
Detection of moving objects by independent component analysis
ACCV'06 Proceedings of the 7th Asian conference on Computer Vision - Volume Part II
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We propose an image processing algorithm for detecting human in outdoor scenes containing changeful background. In this work, regions extracted through background subtraction procedure are accurately classified into human and others by motion analysis in the three dimensional feature space constructed by the spatial uniqueness of image motion F驴, the temporal uniqueness of image motion F驴 , and the temporal motion continuity F驴. Evaluation test proved that proposed algorithm can reduce the error rates of both false positive and false negative to about 1/3 compared with a conventional method. We also tested by a PC-based real-time system over two weeks in real environments, that resulted in its false negative error rate of less than 1% and false positive error number of less than 3 times per day.