The Recognition of Human Movement Using Temporal Templates
IEEE Transactions on Pattern Analysis and Machine Intelligence
The Representation and Recognition of Human Movement Using Temporal Templates
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
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
Object Recognition with Features Inspired by Visual Cortex
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Towards Generic Detection of Unusual Events in Video Surveillance
AVSS '09 Proceedings of the 2009 Sixth IEEE International Conference on Advanced Video and Signal Based Surveillance
A tutorial on particle filters for online nonlinear/non-GaussianBayesian tracking
IEEE Transactions on Signal Processing
Estimation of number of people in crowded scenes using perspective transformation
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Tracking video objects in cluttered background
IEEE Transactions on Circuits and Systems for Video Technology
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This paper provides a new method that generates automatically pseudo Euclidian distances (PED) from the trigonometrically treatments of motion history blobs (MHB) obtained from motion history images (MHI) to extract efficient image features, which are pertinent to video events detection (VED). Given a point with its direction of motion where the point coincides the center of a circle. How far the point can virtually travel inside the circle with that direction? That virtual distance is called pseudo Euclidian distance . PED, would be potentially used in wide variety of computer vision applications, remains the main contribution of this paper. To show the interest of the usage of PED, we have proposed a PED based methodology for VED and the detection results of some events at TRECVID'08 in real videos have been demonstrated.