Introduction to statistical pattern recognition (2nd ed.)
Introduction to statistical pattern recognition (2nd ed.)
CONDENSATION—Conditional Density Propagation forVisual Tracking
International Journal of Computer Vision
An HMM-Based Threshold Model Approach for Gesture Recognition
IEEE Transactions on Pattern Analysis and Machine Intelligence
Statistical color models with application to skin detection
International Journal of Computer Vision
Dynamic Time Warping for Off-Line Recognition of a Small Gesture Vocabulary
RATFG-RTS '01 Proceedings of the IEEE ICCV Workshop on Recognition, Analysis, and Tracking of Faces and Gestures in Real-Time Systems (RATFG-RTS'01)
Histograms of Oriented Gradients for Human Detection
CVPR '05 Proceedings of the 2005 IEEE Computer Society Conference on Computer Vision and Pattern Recognition (CVPR'05) - Volume 1 - Volume 01
Robust hand tracking using a simple color classification technique
VRCAI '08 Proceedings of The 7th ACM SIGGRAPH International Conference on Virtual-Reality Continuum and Its Applications in Industry
STARS: Sign tracking and recognition system using input-output HMMs
Pattern Recognition Letters
Vision-Based Hand Gesture Recognition Using PCA+Gabor Filters and SVM
IIH-MSP '09 Proceedings of the 2009 Fifth International Conference on Intelligent Information Hiding and Multimedia Signal Processing
Tracking of human hands and faces through probabilistic fusion of multiple visual cues
ICVS'08 Proceedings of the 6th international conference on Computer vision systems
FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
Real time hand tracking by combining particle filtering and mean shift
FGR' 04 Proceedings of the Sixth IEEE international conference on Automatic face and gesture recognition
Proceedings of the 11th Brazilian Symposium on Human Factors in Computing Systems
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Hand gesture recognition is an important aspect in Human-Computer interaction, and can be used in various applications, such as virtual reality and computer games. In this paper, we propose a real time hand gesture recognition system. It includes three major procedures: detection, tracking and recognition. In hand detection stage, an open hand is detected by the histograms of oriented gradient and AdaBoost method. The hand detector is trained by the AdaBoost algorithm with HOG features. A contour based tracker is applied in combining condensation and partitioned sampling. After a hand is detected in the image, the tracker can track the hand contour in real time. During the tracking, the trajectory is saved to perform hand gesture recognition in the last stage. Recognition of the hand moving trajectory is implemented by hidden Markov models. Several HMMs are trained in advance, and the results from the tracking stage are then recognized using the trained HMMs. Experiments have been conducted to validate the performance of the proposed system. Under normal webcam it can recognize the predefined gestures quickly and precisely. As it is easy to develop other hand gestures, the proposed system has good potential in many applications.