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Proceedings Paper

Adaptive key frame extraction from RGB-D for hand gesture recognition
Author(s): Hanni Jiang; Xing Ma; Wenyang Li; Shaohu Ding; Chunyang Mu
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Paper Abstract

Sign language is described by their significance primarily hand posture changes. But traditional colour-based detection methods are possible be influenced by complex background, skin tones and other parts of body. In order to overcome such problems, this article adopted the method based on RGB-D to detect the gesture area in the video. Then, the adaptively extracting key frame of sign language is adopted, according to the change of gesture area. So the problem is converted into obtaining the standard static gesture image. Then the identification results are sent to NAO robot. Well the human-robot interaction is completed. Experimental results showed that combination of colour space and depth threshold can greatly reduce the influence of complex background and skin colour region. Key frame extraction is a steady foundation for improving the rate of hand gesture recognition.

Paper Details

Date Published: 9 August 2018
PDF: 6 pages
Proc. SPIE 10806, Tenth International Conference on Digital Image Processing (ICDIP 2018), 108060K (9 August 2018); doi: 10.1117/12.2502953
Show Author Affiliations
Hanni Jiang, North Minzu Univ. (China)
Xing Ma, North Minzu Univ. (China)
Wenyang Li, North Minzu Univ. (China)
Shaohu Ding, North Minzu Univ. (China)
Chunyang Mu, North Minzu Univ. (China)

Published in SPIE Proceedings Vol. 10806:
Tenth International Conference on Digital Image Processing (ICDIP 2018)
Xudong Jiang; Jenq-Neng Hwang, Editor(s)

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