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• W2889663447 abstract "In the process of the traditional hand gesture recognition, complex backgrounds, illumination and hand gesture changes in space can seriously affect the accuracy of the dynamic hand gesture recognition. In this paper, an improved dynamic hand gesture recognition method based on Three-dimensional Time of Flight (3D-TOF) camera is proposed. Firstly, an adaptive segmentation algorithm is used for the hand gesture segmentation combining the frame difference method and the depth threshold. Then a dynamic hand gesture recognition algorithm based on the three-dimensional (3D) spatial trajectory feature and Hidden Markov Model (HMM) is proposed which takes full advantage of the depth data. And in order to improve the recognition rate of the dynamic hand gesture, the misidentified samples are trained again. Experimental results show that the algorithms proposed in this paper have a high recognition rate of the dynamic hand gestures and a good robustness to the different backgrounds and illumination." @default.
• W2889663447 created "2018-09-27" @default.
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• W2889663447 date "2018-01-01" @default.
• W2889663447 modified "2023-09-24" @default.
• W2889663447 title "Dynamic Hand Gesture Recognition Based on the Three-Dimensional Spatial Trajectory Feature and Hidden Markov Model" @default.
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• W2889663447 doi "https://doi.org/10.1007/978-981-13-2384-3_52" @default.
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