Pfinder: Real-Time Tracking of the Human Body
IEEE Transactions on Pattern Analysis and Machine Intelligence
Model-Based Localisation and Recognition of Road Vehicles
International Journal of Computer Vision
W4: Real-Time Surveillance of People and Their Activities
IEEE Transactions on Pattern Analysis and Machine Intelligence
Moving Target Classification and Tracking from Real-time Video
WACV '98 Proceedings of the 4th IEEE Workshop on Applications of Computer Vision (WACV'98)
Semantic concept mining in cricket videos for automated highlight generation
Multimedia Tools and Applications
A multi-view visual surveillance system based on angle coverage
Proceedings of the 8th ACM Conference on Embedded Networked Sensor Systems
A survey of vision-based methods for action representation, segmentation and recognition
Computer Vision and Image Understanding
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In this paper we present an algorithm for real-time object classification and human activity recognition which can help to made intelligent video surveillance systems for human behavior analysis. The proposed method makes use of object silhouettes to classify objects and activity of humans present in a scene monitored by a dynamic camera. An statical background subtraction method is used for object segmentation. The matching templates are constructed using the motion history images for classify objects into classes like human, human group and vehicle; and object shape information for different human activities in a video. Experimental results demonstrate that the proposed method can recognize these activities accurately.