CBAIVL '00 Proceedings of the IEEE Workshop on Content-based Access of Image and Video Libraries (CBAIVL'00)
Gait-Based Recognition of Humans Using Continuous HMMs
FGR '02 Proceedings of the Fifth IEEE International Conference on Automatic Face and Gesture Recognition
Recognizing Human Actions: A Local SVM Approach
ICPR '04 Proceedings of the Pattern Recognition, 17th International Conference on (ICPR'04) Volume 3 - Volume 03
Hardware Acceleration of Hidden Markov Model Decoding for Person Detection
Proceedings of the conference on Design, Automation and Test in Europe - Volume 3
Human Action Recognition Using Multi-View Image Sequences Features
FGR '06 Proceedings of the 7th International Conference on Automatic Face and Gesture Recognition
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
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
View-Invariant Human Action Detection Using Component-Wise HMM of Body Parts
AMDO '08 Proceedings of the 5th international conference on Articulated Motion and Deformable Objects
Towards Real-Time Human Action Recognition
IbPRIA '09 Proceedings of the 4th Iberian Conference on Pattern Recognition and Image Analysis
An efficient approach for multi-view human action recognition based on bag-of-key-poses
HBU'12 Proceedings of the Third international conference on Human Behavior Understanding
Human action recognition optimization based on evolutionary feature subset selection
Proceedings of the 15th annual conference on Genetic and evolutionary computation
Silhouette-based human action recognition using sequences of key poses
Pattern Recognition Letters
| Hi-index | 0.00 |
This paper describes an experimental study about a robust contour feature (shape-context) for using in action recognition based on continuous hidden Markov models (HMM). We ran different experimental setting using the KTH's database of actions. The image contours are extracted using a standard algorithm. The shape-contextfeature vector is build from of histogram of a set ofnon-overlapping regions in the image. We show that the combined use of HMM and this feature gives equivalent o better results, in term of action detection, that current approaches in the literature.