A Real Time Vision-Based Hand Gestures Recognition System
- Cite this paper as:
- Shi L., Wang Y., Li J. (2010) A Real Time Vision-Based Hand Gestures Recognition System. In: Cai Z., Hu C., Kang Z., Liu Y. (eds) Advances in Computation and Intelligence. ISICA 2010. Lecture Notes in Computer Science, vol 6382. Springer, Berlin, Heidelberg
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.
Keywordshand detection hand tracking hand gesture recognition
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