Skip to Main Content
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 F1, the temporal uniqueness of image motion F2, and the temporal motion continuity F3. Evaluation test proved that proposed algorithm could reduce the error rates of both false positive and false negative to about 1/3 compared with a conventional method. We also tested it in 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.
Pattern Recognition, 2004. ICPR 2004. Proceedings of the 17th International Conference on (Volume:4 )
Date of Conference: 23-26 Aug. 2004