A survey on vision-based hand gesture recognition

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Abstract

Hand gesture recognition is regarded as an important part of artificial intelligence. A great effort was put into human-computer interaction so that hand gesture recognition is gradually becoming a developed technology. In light of the utilization of mouse and keyboard, the increasing needs of human-computer interaction cannot be met; hindrance turns out to be increasingly genuine. In this paper, we reviewed previous investigations of vision-based gesture recognition and summarized their findings. This paper compares the most common human-computer interaction products in recent years, which can be used to capture gesture data. Then we started with the classification of gestures and summarized the research of visual gesture recognition based on static and dynamic gestures. The gesture representations we summarized includes appearance-based and 3D model-based methods. We also introduced the applications of the two kinds of hand gestures recognition in the papers of recent years. A possible classification methods was put forward to improve the performance of gesture recognition. The goal of this paper is to summarize the current technology and research results and compare the differences and the advantage of different hand gesture recognition methods, which will contribute to the following research.

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Wang, T., Li, Y., Hu, J., Khan, A., Liu, L., Li, C., … Ran, M. (2018). A survey on vision-based hand gesture recognition. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11010 LNCS, pp. 219–231). Springer Verlag. https://doi.org/10.1007/978-3-030-04375-9_19

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