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
Model-Based Recognition of 3D Objects from Single Images
IEEE Transactions on Pattern Analysis and Machine Intelligence
The Recognition of Human Movement Using Temporal Templates
IEEE Transactions on Pattern Analysis and Machine Intelligence
View-Invariant Representation and Recognition of Actions
International Journal of Computer Vision
Multi Feature Path Modeling for Video Surveillance
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 2 - Volume 02
Semantic-level Understanding of Human Actions and Interactions using Event Hierarchy
CVPRW '04 Proceedings of the 2004 Conference on Computer Vision and Pattern Recognition Workshop (CVPRW'04) Volume 1 - Volume 01
Actions Sketch: A Novel Action Representation
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Detecting Irregularities in Images and in Video
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
Behaviour Understanding in Video: A Combined Method
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
View Invariance for Human Action Recognition
International Journal of Computer Vision
A survey of advances in vision-based human motion capture and analysis
Computer Vision and Image Understanding - Special issue on modeling people: Vision-based understanding of a person's shape, appearance, movement, and behaviour
Advances in view-invariant human motion analysis: a review
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Decomposition of human motion into dynamics-based primitives with application to drawing tasks
Automatica (Journal of IFAC)
Learning motion patterns in unstructured scene based on latent structural information
Journal of Visual Languages and Computing
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The semantic analysis of the human behavior in video streaming is still an open issue for the computer vision research community, especially when real-time analysis of complex scenes is concerned. The researchers' community has achieved many progresses in this field. A popular class of approaches has been devised to enhance the quality of the semantic analysis by exploiting some background knowledge about scene and/or the human behavior, thus narrowing the huge variety of possible behavioral patterns by focusing on a specific narrow domain. Aim of this paper is to present an innovative method for semantic analysis of human behavior in video surveillance systems. Typically, this kind of systems are composed of a set of fixed cameras each one monitoring a fixed area. In the proposed methodology, the actions performed by the human beings are described by means of symbol strings. For each camera a grammar is defined to classify the strings of symbols describing the various behaviors. This system proposes a generative approach to human behavior description so it does not require a learning stage. Another advantage of this approach consists in the simplicity of the scene and motion descriptions so that the behavior analysis will have limited computational complexity due to the intrinsic nature both of the representations and the related operations used to manipulate them. This methodology has been used to implement a system to classify human behaviors in a scene. The results are discussed in this paper and they seem to be encouraging.