A Computational Approach to Edge Detection
IEEE Transactions on Pattern Analysis and Machine Intelligence
Vision-Based Gesture Recognition: A Review
GW '99 Proceedings of the International Gesture Workshop on Gesture-Based Communication in Human-Computer Interaction
Aging in place: fall detection and localization in a distributed smart camera network
Proceedings of the 15th international conference on Multimedia
An intelligent video system for vehicle localization and tracking in police cars
Proceedings of the 2009 ACM symposium on Applied Computing
3D Human Motion Tracking with a Coordinated Mixture of Factor Analyzers
International Journal of Computer Vision
Optimization and Filtering for Human Motion Capture
International Journal of Computer Vision
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The use of video cameras in police cars has been found to have significant value and the number of such installed systems has been increasing. In addition to recording the events in routine traffic stops for later use in legal settings, in-car video cameras can be used to analyze in real-time or near real-time to detect critical events and notify police headquarters for help. This paper presents methods for detecting critical events in such police car videos. The specific critical events are person running out of a stopped car and officer falling down while approaching a stopped car. In the above situations, the aim is to alert the control center immediately for backup forces, especially in the last example when the officer is incapacitated. In order to implement real-time video processing so that a quick response can be generated without employing complex, slow, and brittle video processing algorithms, we use the reduced spatiotemporal representation (1D projection profile) and Hidden Markov Model to detect these events. The methods are tested on many video shots under various environmental and illumination conditions.