The Quality of Training Sample Estimates of the Bhattacharyya Coefficient
IEEE Transactions on Pattern Analysis and Machine Intelligence
Instance-Based Learning Algorithms
Machine Learning
Real-Time Detection of Camera Tampering
AVSS '06 Proceedings of the IEEE International Conference on Video and Signal Based Surveillance
Review: Ambient intelligence: Technologies, applications, and opportunities
Pervasive and Mobile Computing
Ambient intelligence - a state of the art from artificial intelligence perspective
EPIA'07 Proceedings of the aritficial intelligence 13th Portuguese conference on Progress in artificial intelligence
Plans and planning in smart homes
Designing Smart Homes
A motion detection system for video surveillance
Joint Proceedings of the Workshop on AI Problems and Approaches for Intelligent Environments and Workshop on Semantic Cities
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Home automation poses requirements, which are typically solved by AI methods. The paper focuses on the problem of protecting video-surveillance systems against tampering actions, and proposes a new algorithm. This is based on a model of the environment observed by the camera, which must be protected. The model is automatically learned by observing the video stream generated by the camera. The method is now implemented in a commercial system are the results reported from seven experimental sites shows an excellent performance outperforming state of the art algorithms described in the literature.