尺度空间特征下人机交互多姿态三维手势智能识别OA

In allusion to the diversity of gesture postures,scale variations,and the interference of complex backgrounds in human-computer interaction,a method of intelligent multi-pose three-dimensional gesture recognition for human-computer interaction under scale spatial features is proposed.The three-dimensional gesture point cloud is constructed and converted into a binary voxel grid.The gesture features with spatial distribution features are extracted by combining the pyramid multi-scale structure and the SIFT descriptor.The three-dimensional convolutional network is used to regression the heat map of the joint points to realize the precise positioning,and the temporal shift module and the LSTM network are introduced to model the dynamic sequence of gestures,so as to realize the real-time intelligent recognition of multi-pose gestures.The experimental results prove that the comprehensive recognition confidence level of this method for 10 types of interactive gestures can reach up to 99.68%.In the three scenarios of virtual games,office work and teaching,the recognition stability is 97.7%,96.38%and 98.67%,and the anti-interference ability is 94.99%,93.85%and 95.98%,which can achieve high-precision multi-pose three-dimensional gesture intelligent recognition,and provide reliable and natural gesture interaction support for human-computer interaction and virtual reality applications.