The automated mapping of plans for plan recognition
AAAI'94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 2)
The nature of statistical learning theory
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Probabilistic grammars for plan recognition
Probabilistic grammars for plan recognition
Pattern Classification (2nd Edition)
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Segmenting motion capture data into distinct behaviors
GI '04 Proceedings of the 2004 Graphics Interface Conference
Modeling Physical Capabilities of Humanoid Agents Using Motion Capture Data
AAMAS '04 Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 1
Recognizing Human Actions: A Local SVM Approach
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 3 - Volume 03
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 2 - Volume 02
Learning and inferring transportation routines
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
High-level goal recognition in a wireless LAN
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
A general model for online probabilistic plan recognition
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Propagation networks for recognition of partially ordered sequential action
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
A new model of plan recognition
UAI'99 Proceedings of the Fifteenth conference on Uncertainty in artificial intelligence
Multi-agent strategic modeling in a robotic soccer domain
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
An integrated approach to high-level information fusion
Information Fusion
Hierarchical Classifiers for Complex Spatio-temporal Concepts
Transactions on Rough Sets IX
Simultaneous team assignment and behavior recognition from spatio-temporal agent traces
AAAI'06 Proceedings of the 21st national conference on Artificial intelligence - Volume 1
Incorporating observer biases in keyhole plan recognition (efficiently!)
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 2
Behavior Analysis Based on Coordinates of Body Tags
AmI '09 Proceedings of the European Conference on Ambient Intelligence
Identification of gait patterns related to health problems of elderly
UIC'10 Proceedings of the 7th international conference on Ubiquitous intelligence and computing
Automatic recognition of gait-related health problems in the elderly using machine learning
Multimedia Tools and Applications
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This paper presents a cost minimization approach to the problem of human behavior recognition. Using full-body motion capture data acquired from human subjects, our system recognizes the behaviors that a human subject is performing from a set of military maneuvers, based on the subject's motion type and proximity to landmarks. Low-level motion classification is performed using support vector machines (SVMs) and a hidden Markov Model (HMM); output from the classifier is used as an input feature for the behavior recognizer. Given the dynamic and highly reactive nature of the domain, our system must handle behavior sequences that are frequently interrupted and often interleaved. To recognize such behavior sequences, we employ dynamic programming in conjunction with a behavior transition cost function to efficiently select the most parsimonious explanation for the human's actions. We demonstrate that our system is robust to action classification errors and deviations by the human subject from the expected set of behaviors. Our approach is well suited for incorporation into synthetic agents that cooperate or compete against human subjects in virtual reality training environments.