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However, the current gesture processing methods for RGB-D images still can not fully utilize the information contained. Aiming at the above problems, this paper studies the feature extraction method of RGB-D image, and proposes a multimodal and multilevel feature extraction method. By extracting multimodal and multilevel image features for mapping and splicing, the utilization of RGB-D image information and the accuracy in recognition are improved effectively. Finally, the experiments verified the effectiveness and robustness of the proposed method based on the self-built gesture database. Compared and analyzed with several other RGB-D processing methods, the processing method of this paper is more advanced and effective, and can achieve better results in gesture recognition.<\/jats:p>","DOI":"10.3233\/jifs-179541","type":"journal-article","created":{"date-parts":[[2019,12,17]],"date-time":"2019-12-17T10:41:25Z","timestamp":1576579285000},"page":"2539-2550","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":48,"title":["Gesture recognition based on multilevel multimodal feature fusion"],"prefix":"10.1177","volume":"38","author":[{"given":"Jinrong","family":"Tian","sequence":"first","affiliation":[{"name":"Key Laboratory of Metallurgical Equipment and Control Technology of Ministry of Education, Wuhan University of Science and Technology, Wuhan, China"}]},{"given":"Wentao","family":"Cheng","sequence":"additional","affiliation":[{"name":"Key Laboratory of Metallurgical Equipment and Control Technology of 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