Abstract
Gesture recognition is an indispensable part of the human–computer interaction technology. In this paper, the research on dynamic gesture recognition technology based on multi feature fusion is studied. While identifying the posture using SVM, the dynamic gesture track feature is extracted and recognized using Gaussian pyramid optical flow algorithm. Then we’ll get the final recognition results by information fusion on decision level. Finally through the contrast experiment to prove the dynamic gesture recognition algorithm in the paper has higher gesture recognition rate.
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Yu, M., Liu, Y. (2018). Research on Dynamic Gesture Recognition Based on Multi Feature Fusion. In: Liang, Q., Mu, J., Wang, W., Zhang, B. (eds) Communications, Signal Processing, and Systems. CSPS 2016. Lecture Notes in Electrical Engineering, vol 423. Springer, Singapore. https://doi.org/10.1007/978-981-10-3229-5_78
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DOI: https://doi.org/10.1007/978-981-10-3229-5_78
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