Title :
Visual gesture recognition with color segmentation and support vector machines
Author :
Hang, Zhou ; Qiuqi, Ruan
Author_Institution :
Inst. of Inf. Sci., Beijing Jiaotong Univ., China
fDate :
31 Aug.-4 Sept. 2004
Abstract :
We present a two-stage hand gesture recognition system. It includes a novel approach for real-time skin segmentation in video using color space. The approach enables robust segmentation of skin-colored patches despite certain illumination conditions. We give a skin range to broaden the field of skin color to deal with occlusion and effect of background. The performance of our algorithm was approved to the segmentation obtained using static color model. Then we use approved linear SVM learning algorithm to train pixel data set and established a structure decision tree. Finally, the result of recognition system achieved accuracy for testing sequence at 92%.
Keywords :
decision trees; gesture recognition; image classification; image colour analysis; image segmentation; image sequences; learning systems; support vector machines; color space; decision tree structure; linear SVM learning algorithm; occlusion; pixel training data set; real-time skin segmentation; recognition system; segmentation; sequence; skin-colored patch; support vector machine; two-stage hand gesture recognition system; visual gesture recognition; Colored noise; Data mining; Fingers; Information science; Shape; Skin; Support vector machine classification; Support vector machines; Training data; Wrist;
Conference_Titel :
Signal Processing, 2004. Proceedings. ICSP '04. 2004 7th International Conference on
Print_ISBN :
0-7803-8406-7
DOI :
10.1109/ICOSP.2004.1441598