A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Motion segmentation and pose recognition with motion history gradients
Machine Vision and Applications - Special issue: IEEE WACV
Foreground object detection from videos containing complex background
MULTIMEDIA '03 Proceedings of the eleventh ACM international conference on Multimedia
Activity Summarisation and Fall Detection in a Supportive Home Environment
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 4 - Volume 04
Fall Detection from Human Shape and Motion History Using Video Surveillance
AINAW '07 Proceedings of the 21st International Conference on Advanced Information Networking and Applications Workshops - Volume 02
Midground object detection in real world video scenes
AVSS '07 Proceedings of the 2007 IEEE Conference on Advanced Video and Signal Based Surveillance
Image segmentation in video sequences: a probabilistic approach
UAI'97 Proceedings of the Thirteenth conference on Uncertainty in artificial intelligence
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Video surveillance systems are becoming increasingly popular due to the emergence of high-speed wireless Internet (such as WiMax and LTE), bandwidth-efficient video compression schemes (such as H.264), and low-cost (and high-resolution) IP video cameras. This paper presents two applications of an advanced surveillance system, specifically in suspicious activity detection and human fall detection, for both indoor and outdoor environments. The implemented prototype captures and analyzes live high-definition (HD) video that is streamed from a remote camera. We will show that by combining the strengths of ellipse modeling and shadow removal, and other novel algorithms, the false alarms in the detection can be significantly reduced.