Probabilistic Languages: A Review and Some Open Questions
ACM Computing Surveys (CSUR)
Human Motion: Modeling and Recognition of Actions and Interactions
3DPVT '04 Proceedings of the 3D Data Processing, Visualization, and Transmission, 2nd International Symposium
A robust architecture for distributed inference in sensor networks
IPSN '05 Proceedings of the 4th international symposium on Information processing in sensor networks
XYZ: a motion-enabled, power aware sensor node platform for distributed sensor network applications
IPSN '05 Proceedings of the 4th international symposium on Information processing in sensor networks
Learning and inferring transportation routines
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
View-invariant modeling and recognition of human actions using grammars
WDV'05/WDV'06/ICCV'05/ECCV'06 Proceedings of the 2005/2006 international conference on Dynamical vision
A survey on visual surveillance of object motion and behaviors
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Address-event imagers for sensor networks: evaluation and modeling
Proceedings of the 5th international conference on Information processing in sensor networks
BehaviorScope: Real-Time Remote Human Monitoring Using Sensor Networks
IPSN '08 Proceedings of the 7th international conference on Information processing in sensor networks
Activity recognition via user-trace segmentation
ACM Transactions on Sensor Networks (TOSN)
A wireless sensor network architecture and its application in an assistive environment
Proceedings of the 1st international conference on PErvasive Technologies Related to Assistive Environments
Extracting spatiotemporal human activity patterns in assisted living using a home sensor network
Proceedings of the 1st international conference on PErvasive Technologies Related to Assistive Environments
Towards precision monitoring of elders for providing assistive services
Proceedings of the 1st international conference on PErvasive Technologies Related to Assistive Environments
Adaptive sensor/actuator networks for tracking environment control behaviors
CSTST '08 Proceedings of the 5th international conference on Soft computing as transdisciplinary science and technology
Distributed image search in camera sensor networks
Proceedings of the 6th ACM conference on Embedded network sensor systems
A methodology for extracting temporal properties from sensor network data streams
Proceedings of the 7th international conference on Mobile systems, applications, and services
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Sensory grammars for sensor networks
Journal of Ambient Intelligence and Smart Environments
Fence monitoring: experimental evaluation of a use case for wireless sensor networks
EWSN'07 Proceedings of the 4th European conference on Wireless sensor networks
The BehaviorScope framework for enabling ambient assisted living
Personal and Ubiquitous Computing
Specification and verification of complex location events with panoramic
Pervasive'10 Proceedings of the 8th international conference on Pervasive Computing
Sensory grammars for sensor networks
Journal of Ambient Intelligence and Smart Environments
Shopping behavior recognition using a language modeling analogy
Pattern Recognition Letters
Testbeds for ubiquitous robotics: A survey
Robotics and Autonomous Systems
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The ability of a sensor network to parse out observable activities into a set of distinguishable actions is a powerful feature that can potentially enable many applications of sensor networks to everyday life situations. In this paper we introduce a framework that uses a hierarchy of Probabilistic Context Free Grammars (PCFGs) to perform such parsing. The power of the framework comes from the hierarchical organization of grammars that allows the use of simple local sensor measurements for reasoning about more macroscopic behaviors. Our presentation describes how to use a set of phonemes to construct grammars and how to achieve distributed operation using a messaging model. The proposed framework is flexible. It can be mapped to a network hierarchy or can be applied sequentially and across the network to infer behaviors as they unfold in space and time. We demonstrate this functionality by inferring simple motion patterns using a sequence of simple direction vectors obtained from our camera sensor network testbed.