Gesture recognition method, system and device based on augmented reality
A gesture recognition and augmented reality technology, applied in the field of information processing, can solve the problems of low gesture recognition rate and poor real-time gesture recognition.
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Embodiment 1
[0065] see figure 1 , figure 1 It is a schematic flowchart of an augmented reality-based gesture recognition method provided by the embodiment of the present application. Depend on figure 1 It can be seen that the gesture recognition method based on augmented reality in this embodiment mainly includes the following steps:
[0066] S1: Acquire a gesture depth map and gesture depth information of a human hand, where the gesture depth map includes static video frames and dynamic video frames, and the gesture depth information includes joint point coordinates.
[0067] In this embodiment, a kinect somatosensory device may be used to obtain gesture depth information and a gesture depth map of a human hand. Use the bone information of the kinect somatosensory device to obtain the joint point coordinates of the human hand, that is, the depth coordinates, and obtain the gesture depth map.
[0068] In this embodiment, the gesture depth map includes static video frames and dynamic v...
Embodiment 2
[0109] exist figure 1 On the basis of the illustrated embodiment see figure 2 , figure 2 It is a schematic structural diagram of an augmented reality-based gesture recognition system provided by the embodiment of the present application. Depend on figure 2 It can be seen that the gesture recognition system based on augmented reality in this embodiment mainly includes seven parts: an information acquisition module, a set classification module, a cutting module, an optimization module, a recognition model building module, a testing module and a recognition module.
[0110] Wherein, the information acquisition module is used to acquire the gesture depth map and gesture depth information of the human hand, the gesture depth map includes static video frames and dynamic video frames, and the gesture depth information includes joint point coordinates. The set classification module is used to divide the gesture depth map into a training set and a test set according to the ratio ...
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