A Step Towards Unification of Syntactic and Statistical Pattern Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence - Special memorial issue for Professor King-Sun Fu
Pattern recognition: statistical, structural and neural approaches
Pattern recognition: statistical, structural and neural approaches
Fundamentals of speech recognition
Fundamentals of speech recognition
Bayesian learning of probabilistic language models
Bayesian learning of probabilistic language models
Pfinder: Real-Time Tracking of the Human Body
IEEE Transactions on Pattern Analysis and Machine Intelligence
A State-Based Approach to the Representation and Recognition of Gesture
IEEE Transactions on Pattern Analysis and Machine Intelligence
Statistical Language Learning
Understanding manipulation in video
FG '96 Proceedings of the 2nd International Conference on Automatic Face and Gesture Recognition (FG '96)
Multiobject Behavior Recognition by Event Driven Selective Attention Method
IEEE Transactions on Pattern Analysis and Machine Intelligence
Event Detection and Analysis from Video Streams
IEEE Transactions on Pattern Analysis and Machine Intelligence
Vision-Based Gesture Recognition: A Review
GW '99 Proceedings of the International Gesture Workshop on Gesture-Based Communication in Human-Computer Interaction
Learning temporal, relational, force-dynamic event definitions from video
Eighteenth national conference on Artificial intelligence
Reconstructing force-dynamic models from video sequences
Artificial Intelligence
Mining models of human activities from the web
Proceedings of the 13th international conference on World Wide Web
Using Interaction Signatures to Find and Label Chairs and Floors
IEEE Pervasive Computing
Aggregate operators in probabilistic databases
Journal of the ACM (JACM)
Probabilistic grounding of situated speech using plan recognition and reference resolution
ICMI '05 Proceedings of the 7th international conference on Multimodal interfaces
Task oriented facial behavior recognition with selective sensing
Computer Vision and Image Understanding
Sequential inference with reliable observations: learning to construct force-dynamic models
Artificial Intelligence
Robust recognition and segmentation of human actions using HMMs with missing observations
EURASIP Journal on Applied Signal Processing
Conceptual representations between video signals and natural language descriptions
Image and Vision Computing
Searching for Complex Human Activities with No Visual Examples
International Journal of Computer Vision
Applying Space State Models in Human Action Recognition: A Comparative Study
AMDO '08 Proceedings of the 5th international conference on Articulated Motion and Deformable Objects
Spatially Constrained Grammars for Mobile Intention Recognition
Proceedings of the international conference on Spatial Cognition VI: Learning, Reasoning, and Talking about Space
Gesture Recognition for a Webcam-Controlled First Person Shooter
ISVC '08 Proceedings of the 4th International Symposium on Advances in Visual Computing, Part II
International Journal of Computer Vision
CASEE: a hierarchical event representation for the analysis of videos
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
Multiple agent event detection and representation in videos
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 1
Journal of Artificial Intelligence Research
Grounding the lexical semantics of verbs in visual perception using force dynamics and event logic
Journal of Artificial Intelligence Research
Sequential inference with reliable observations: Learning to construct force-dynamic models
Artificial Intelligence
Task oriented facial behavior recognition with selective sensing
Computer Vision and Image Understanding
Learning atomic human actions using variable-length Markov models
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics - Special issue on human computing
Analysis of multi-agent activity using petri nets
Pattern Recognition
A self-referential perceptual inference framework for video interpretation
ICVS'03 Proceedings of the 3rd international conference on Computer vision systems
Recurrent Bayesian network for the recognition of human behaviors from video
ICVS'03 Proceedings of the 3rd international conference on Computer vision systems
Follow the beat? understanding conducting gestures from video
ISVC'07 Proceedings of the 3rd international conference on Advances in visual computing - Volume Part I
A cognitive vision system for action recognition in office environments
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
A survey of vision-based methods for action representation, segmentation and recognition
Computer Vision and Image Understanding
Multifactor feature extraction for human movement recognition
Computer Vision and Image Understanding
Approximate reasoning and finite state machines to the detection of actions in video sequences
International Journal of Approximate Reasoning
Unsupervised action classification using space-time link analysis
Journal on Image and Video Processing
Intent inference via syntactic tracking
Digital Signal Processing
Composition of complex motion models from elementary human motions
AMDO'06 Proceedings of the 4th international conference on Articulated Motion and Deformable Objects
Human activity recognition in videos: a systematic approach
IDEAL'06 Proceedings of the 7th international conference on Intelligent Data Engineering and Automated Learning
Intelligent multi-camera video surveillance: A review
Pattern Recognition Letters
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A new approach to the recognition of temporal behaviors and activities is presented. The fundamental idea, inspired by work in speech recognition, is to divide the inference problem into two levels. The lower level is performed using standard independent probabilistic temporal event detectors such as hidden Markov models (HMMs) to propose candidate detections of low level temporal features. The outputs of these detectors provide the input stream for a stochastic context-free grammar parsing mechanism. The grammar and parser provide longer range temporal constraints, disambiguate uncertain low level detections, and allow the inclusion of a priori knowledge about the structure of temporal events in a given domain. To achieve such a system we provide techniques for generating a discrete symbol stream from continuous low level detectors and for enforcing temporal exclusion constraints during parsing. We demonstrate the approach in several experiments using both visual and other sensing data.