The visual analysis of human movement: a survey
Computer Vision and Image Understanding
Detecting Human Motion with Support Vector Machines
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 2 - Volume 02
Histograms of Oriented Gradients for Human Detection
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Shape and the Stereo Correspondence Problem
International Journal of Computer Vision
A Roadmap to the Integration of Early Visual Modules
International Journal of Computer Vision
Pedestrian Detection via Classification on Riemannian Manifolds
IEEE Transactions on Pattern Analysis and Machine Intelligence
Human detection using oriented histograms of flow and appearance
ECCV'06 Proceedings of the 9th European conference on Computer Vision - Volume Part II
Ensemble of Multiple Pedestrian Representations
IEEE Transactions on Intelligent Transportation Systems
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An approach to detect moving and standing human from video is proposed in this paper. Human detection from videos is a difficult problem because of motion of human, camera and background. In order to detect moving human, the dense optical flow is calculated by two consecutive frames, to represent the motion of human. Motion based feature is extracted from optical flow field. It not only represents the global motion caused by the boundary of human body, but also contains local motion caused by the limbs. Motion based feature is combined with histogram of template feature, which is designed to detect standing human, as final feature for detection. Experiment on CAS dataset shows that this feature has more discriminative ability than other motion based feature. Besides, this feature is easier for hardware acceleration, which makes it suitable for real time application.