Simulating humans: computer graphics animation and control
Simulating humans: computer graphics animation and control
The visual analysis of human movement: a survey
Computer Vision and Image Understanding
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
View-Invariant Representation and Recognition of Actions
International Journal of Computer Vision
Periodic Human Motion Description for Sports Video Databases
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 3 - Volume 03
Acquiring and validating motion qualities from live limb gestures
Graphical Models
Recognition of Composite Human Activities through Context-Free Grammar Based Representation
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
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
Vision-based human motion analysis: An overview
Computer Vision and Image Understanding
Recognition of High-level Group Activities Based on Activities of Individual Members
WMVC '08 Proceedings of the 2008 IEEE Workshop on Motion and video Computing
A survey on vision-based human action recognition
Image and Vision Computing
3D Human Action Recognition for Multi-view Camera Systems
3DIMPVT '11 Proceedings of the 2011 International Conference on 3D Imaging, Modeling, Processing, Visualization and Transmission
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This paper presents an approach for modeling human interactions based on existent relationship characteristics between body parts motions and environmental parameters. Human interactions properly cannot be identified without knowing the relations between the objects such as human-robot and human-human. During any human interaction, there are many relations between human body parts and others. In this article a general model to analyse human interactions based on the existent relationships is presented. To study human motion properties, Laban Movement Analysis (LMA), a well-known human motion descriptor is used. This work focused onRelationship's component of the LMA to analyse and formulate human activities related to environment. Bayesian approaches are proper classifiers for the mentioned goal, in order to be able to predict, define the existent dependencies, fuse different types of features and also deal with uncertainty. To present the idea, the model was performed to estimate some human movements and activities related to an object like a robot or another person. The result proves the capability of the approach to model and analyse any human activities related to environment using the LMA framework.