Learning Patterns of Activity Using Real-Time Tracking
IEEE Transactions on Pattern Analysis and Machine Intelligence
A survey of computer vision-based human motion capture
Computer Vision and Image Understanding - Modeling people toward vision-based underatanding of a person's shape, appearance, and movement
Unsupervised Analysis of Human Gestures
PCM '01 Proceedings of the Second IEEE Pacific Rim Conference on Multimedia: Advances in Multimedia Information Processing
Real-Time Online Adaptive Gesture Recognition
RATFG-RTS '99 Proceedings of the International Workshop on Recognition, Analysis, and Tracking of Faces and Gestures in Real-Time Systems
Acoustic Source Location in a Three-Dimensional Space Using Crosspower Spectrum Phase
ICASSP '97 Proceedings of the 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '97) -Volume 1 - Volume 1
Adaptive Blind Signal and Image Processing: Learning Algorithms and Applications
Adaptive Blind Signal and Image Processing: Learning Algorithms and Applications
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
Unsupervised clustering of ambulatory audio and video
ICASSP '99 Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 06
Finding temporal patterns by data decomposition
FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
Discovering clusters in motion time-series data
CVPR'03 Proceedings of the 2003 IEEE computer society conference on Computer vision and pattern recognition
Simultaneous tracking and activity recognition (STAR) using many anonymous, binary sensors
PERVASIVE'05 Proceedings of the Third international conference on Pervasive Computing
Proceedings of the 9th international conference on Multimodal interfaces
The MERL motion detector dataset
Proceedings of the 2007 workshop on Massive datasets
Distributed Activity Recognition with Fuzzy-Enabled Wireless Sensor Networks
DCOSS '08 Proceedings of the 4th IEEE international conference on Distributed Computing in Sensor Systems
Coupling control and human factors in mathematical models of complex systems
Engineering Applications of Artificial Intelligence
Activity recognition in smart homes: from specification to representation
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
Event prediction in a hybrid camera network
ACM Transactions on Sensor Networks (TOSN)
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By analyzing the similarities between bit streams coming from a network of motion detectors, we can recover the network geometry and discover structure in the human behavior being observed. This means that a low-cost network of sensors can provide powerful contextual information to building systems: improving the efficiency of elevators, lighting, heating, and cooling; enhancing safety and security; and opening up new opportunities for human-centered information systems. This paper will show how signal similarity can be used to calibrate a sensor network to accuracies below the resolution of the individual sensors. This is done by analyzing the similarity structures in the unconstrained movement of people in the observed space. We will also present our efficient behavior-learning algorithm that yields 90% correct behavior-detection in data from a sensor network comprised of motion detectors by employing similarity-based clustering to automatically decompose complex activities into detectable sub-classes.