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2017 | OriginalPaper | Buchkapitel

Integrating Color and Depth Cues for Static Hand Gesture Recognition

verfasst von : Jiaming Li, Yulan Guo, Yanxin Ma, Min Lu, Jun Zhang

Erschienen in: Computer Vision

Verlag: Springer Singapore

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Abstract

Recognizing static hand gesture in complex backgrounds is a challenging task. This paper presents a static hand gesture recognition system using both color and depth information. Firstly, the hand region is extracted from complex background based on depth segmentation and skin-color model. The Moore-Neighbor tracing algorithm is then used to obtain hand gesture contour. The k-curvature method is used to locate fingertips and determine the number of fingers, then the angle between fingers are generated as features. The appearance-based features are integrated to the decision tree model for hand gesture recognition. Experiments have been conducted on two gesture recognition datasets. Experimental results show that the proposed method achieves a high recognition accuracy and strong robustness.

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Titel: Integrating Color and Depth Cues for Static Hand Gesture Recognition
verfasst von: Jiaming Li
Yulan Guo
Yanxin Ma
Min Lu
Jun Zhang
Verlag: Springer Singapore
Buch: Computer Vision
Print ISBN: 978-981-10-7298-7

Electronic ISBN: 978-981-10-7299-4

Copyright-Jahr: 2017
DOI: https://doi.org/10.1007/978-981-10-7299-4_24

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