W4: Real-Time Surveillance of People and Their Activities
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fusion of Multiple Tracking Algorithms for Robust People Tracking
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part IV
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
Multi-Scale Gesture Recognition from Time-Varying Contours
ICCV '05 Proceedings of the Tenth IEEE International Conference on Computer Vision (ICCV'05) Volume 1 - Volume 01
FGR '06 Proceedings of the 7th International Conference on Automatic Face and Gesture Recognition
Automatic Gesture Recognition for Intelligent Human-Robot Interaction
FGR '06 Proceedings of the 7th International Conference on Automatic Face and Gesture Recognition
Robust People Tracking with Global Trajectory Optimization
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
Robust multi-target tracking using spatio-temporal context
CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 1
Tracking multiple humans in crowded environment
CVPR'04 Proceedings of the 2004 IEEE computer society conference on Computer vision and pattern recognition
Gaussian mixture model in improved HLS color space for human silhouette extraction
ICAT'06 Proceedings of the 16th international conference on Advances in Artificial Reality and Tele-Existence
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In this paper, we propose gesture recognition in multiple people environment. Our system is divided into two modules: Segmentation and Recognition. In segmentation part, we extract foreground area from input image, and we decide the closest person as a recognition subject. In recognition part, firstly we extract feature point of subject's both hands using contour based method and skin based method. Extracted points are tracked using Kalman filter. We use trajectories of both hands for recognizing gesture. In this paper, we use the simple queue matching method as a recognition method. We also apply our system as an animation system. Our method can select subject effectively and recognize gesture in multiple people environment. Therefore, proposed method can be used for real world application such as home appliance and humanoid robot.