Behavioral Feature Description Method Based on the Vector Module Ratio and Vector Angle of Human Body Structure

IEEE ACCESS(2020)

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摘要
In the field of computer vision, the depth image sequence collected by depth camera is not sensitive to the interference of light, occlusion and background environment. Therefore, in recent years, it is often used to collect behavior data, from which the characteristics of bone joint points are extracted as behavior information. However, it is found that the direct use of joint coordinate information collected by depth camera for behavior recognition is easily affected by individual differences in behavior and changes in shooting distance. Considering the position information of human joints as well as the angle and length information of hidden limbs, based on skeleton data, a behavior feature description method based on the ratio of vector angle and vector mode of human structure is proposed. This method solves the above problems perfectly and obtains ideal results on the self built data set, which is suitable for simple daily behavior recognition.
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关键词
Bones,Feature extraction,Cameras,Physiology,Target tracking,Image sequences,Kinect,description of behavior characteristics,vector module ratio,vector angle of human body structure,BP neural network
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