Gesture Intention Understanding Based on Depth and RGB Data

Yu Feng, Luefeng Chcn*, Wanjuan Su, Kaoru Hirota

*此作品的通讯作者

科研成果: 书/报告/会议事项章节会议稿件同行评审

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摘要

Aiming at the problem that the process of gesture recognition based on color image is greatly affected by environmental factors such as lighting, a gesture intent understanding method based on the fusion of Red-Green-Blue (RGB) data and depth data is proposed. Firstly, the gesture feature extraction based on the Speeded Up Robust Feature (SURF) method after foreground segmentation are used to get gesture information. Then, we apply Backpropagation (BP) neural network to classify and recognize gestures. The final recognition results are obtained through data fusion from recognition results based on both RGB images and depth images. We evaluated the effectiveness of the proposed method through ChaLearn Gesture Database.

源语言英语
主期刊名Proceedings of the 37th Chinese Control Conference, CCC 2018
编辑Xin Chen, Qianchuan Zhao
出版商IEEE Computer Society
9556-9559
页数4
ISBN(电子版)9789881563941
DOI
出版状态已出版 - 5 10月 2018
已对外发布
活动37th Chinese Control Conference, CCC 2018 - Wuhan, 中国
期限: 25 7月 201827 7月 2018

出版系列

姓名Chinese Control Conference, CCC
2018-July
ISSN(印刷版)1934-1768
ISSN(电子版)2161-2927

会议

会议37th Chinese Control Conference, CCC 2018
国家/地区中国
Wuhan
时期25/07/1827/07/18

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引用此

Feng, Y., Chcn, L., Su, W., & Hirota, K. (2018). Gesture Intention Understanding Based on Depth and RGB Data. 在 X. Chen, & Q. Zhao (编辑), Proceedings of the 37th Chinese Control Conference, CCC 2018 (页码 9556-9559). 文章 8483387 (Chinese Control Conference, CCC; 卷 2018-July). IEEE Computer Society. https://doi.org/10.23919/ChiCC.2018.8483387