Learning Patterns of Activity Using Real-Time Tracking
IEEE Transactions on Pattern Analysis and Machine Intelligence
Recognition of Visual Activities and Interactions by Stochastic Parsing
IEEE Transactions on Pattern Analysis and Machine Intelligence
Distributed sensor network for real time tracking
Proceedings of the fifth international conference on Autonomous agents
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
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
Pattern Classification (2nd Edition)
Pattern Classification (2nd Edition)
Habitat monitoring with sensor networks
Communications of the ACM - Wireless sensor networks
An analysis of Bayesian classifiers
AAAI'92 Proceedings of the tenth national conference on Artificial intelligence
Estimating continuous distributions in Bayesian classifiers
UAI'95 Proceedings of the Eleventh conference on Uncertainty in artificial intelligence
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
Activity recognition via user-trace segmentation
ACM Transactions on Sensor Networks (TOSN)
Pervasive '08 Proceedings of the 6th International Conference on Pervasive Computing
Review: Ambient intelligence: Technologies, applications, and opportunities
Pervasive and Mobile Computing
Activity Recognition from Sparsely Labeled Data Using Multi-Instance Learning
LoCA '09 Proceedings of the 4th International Symposium on Location and Context Awareness
Annotating smart environment sensor data for activity learning
Technology and Health Care - Smart Environments: Technology to Support Healthcare
Distributed activity recognition using key sensors
ICACT'09 Proceedings of the 11th international conference on Advanced Communication Technology - Volume 3
Multi-agent smart environments
Journal of Ambient Intelligence and Smart Environments
Coping with multiple residents in a smart environment
Journal of Ambient Intelligence and Smart Environments
An 'object-use fingerprint': the use of electronic sensors for human identification
UbiComp '07 Proceedings of the 9th international conference on Ubiquitous computing
Predicting air quality in smart environments
Journal of Ambient Intelligence and Smart Environments
Mining and monitoring patterns of daily routines for assisted living in real world settings
Proceedings of the 1st ACM International Health Informatics Symposium
Exploiting acoustic source localization for context classification in smart environments
AmI'10 Proceedings of the First international joint conference on Ambient intelligence
Activity knowledge transfer in smart environments
Pervasive and Mobile Computing
Annotating sensor data to identify activities of daily living
ICOST'11 Proceedings of the 9th international conference on Toward useful services for elderly and people with disabilities: smart homes and health telematics
Multi-agent smart environments
Journal of Ambient Intelligence and Smart Environments
Coping with multiple residents in a smart environment
Journal of Ambient Intelligence and Smart Environments
Pervasive and Mobile Computing
An opportunistic activity-sensing approach to save energy in office buildings
Proceedings of the fourth international conference on Future energy systems
ACM Transactions on Intelligent Systems and Technology (TIST) - Survey papers, special sections on the semantic adaptive social web, intelligent systems for health informatics, regular papers
Learning a taxonomy of predefined and discovered activity patterns
Journal of Ambient Intelligence and Smart Environments
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Sensor networks hold the promise of truly intelligent buildings: buildings that adapt to the behavior of their occupants to improve productivity, efficiency, safety, and security. To be practical, such a network must be economical to manufacture, install and maintain. Similarly, the methodology must be efficient and must scale well to very large spaces. Finally, be be widely acceptable, it must be inherently privacy-sensitive. We propose to address these requirements by employing networks of passive infrared (PIR) motion detectors. PIR sensors are inexpensive, reliable, and require very little bandwidth. They also protect privacy since they are neither capable of directly identifying individuals nor of capturing identifiable imagery or audio. However, with an appropriate analysis methodology, we show that they are capable of providing useful contextual information. The methodology we propose supports scalability by adopting a hierarchical framework that splits computation into localized, distributed tasks. To support our methodology we provide theoretical justification for the method that grounds it in the action recognition literature. We also present quantitative results on a dataset that we have recorded from a 400 square meter wing of our laboratory. Specifically, we report quantitative results that show better than 90% recognition performance for low-level activities such as walking, loitering, and turning. We also present experimental results for mid-level activities such as visiting and meeting.