Theoretical Computer Science
A Bayesian Computer Vision System for Modeling Human Interactions
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
Learning variable-length Markov models of behavior
Computer Vision and Image Understanding - Modeling people toward vision-based underatanding of a person's shape, appearance, and movement
Formal Methods for Real-Time Computing
Formal Methods for Real-Time Computing
On sequential Monte Carlo sampling methods for Bayesian filtering
Statistics and Computing
Contour Tracking by Stochastic Propagation of Conditional Density
ECCV '96 Proceedings of the 4th European Conference on Computer Vision-Volume I - Volume I
Color-Based Probabilistic Tracking
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
The Representation and Recognition of Human Movement Using Temporal Templates
CVPR '97 Proceedings of the 1997 Conference on Computer Vision and Pattern Recognition (CVPR '97)
Using Head Movement to Recognize Activity
ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 4
Parameterized Modeling and Recognition of Activities
ICCV '98 Proceedings of the Sixth International Conference on Computer Vision
Kernel Particle Filter for Real-Time 3D Body Tracking in Monocular Color Images
FGR '06 Proceedings of the 7th International Conference on Automatic Face and Gesture Recognition
Hi-index | 0.01 |
This paper addresses the problem of action recognition in meeting videos. A declarative knowledge provided graphically by the user together with person positions extracted by a tracking algorithm are used to generate the data for recognition. The actions have been formally specified using timed automata. The specification was verified on the basis of simulation tests as well as an analysis. The tracking is accomplished using a particle filter built on cues such as color, gradient and shape.