A Method for Pose Estimation of Moving Human Body

Abstract

The invention discloses a method for estimating the posture of a moving human body, which can accurately locate the skeleton points of the human body, effectively obtain the more expressive features of the three-dimensional moving human body, and make the construction more effective and simple. It includes: (1) using the median filter method to preprocess the depth image data, and using the Dijkstra algorithm based on geodesic distance to calibrate the human body pixels; (2) based on the K-means clustering algorithm Based on the regional feature point extraction algorithm, the number of clusters in each class is determined to be 3, and 32 posture features are extracted to represent different human postures; (3) In the training phase, the skeleton point position labeling information is obtained through the PoserPro2012 software, and the synthetic The posture features of 300 frames of virtual human are marked with standard skeleton points. Through the posture feature points of training samples and standard skeleton points, the linear regression model of posture features and skeleton points is calculated to obtain the mapping relationship between posture features and standard skeleton points. .

Description

technical field [0001] The invention belongs to the technical field of computer vision and pattern recognition, and in particular relates to a method for gesture estimation of a moving human body. Background technique [0002] Human pose estimation is an important research direction in the field of computer vision. In the past ten years, the problem of automatically recognizing human poses in image and video sequences has been a research hotspot in the field of computer vision. The main reason for human body pose estimation to become the focus of research is the rapid development of electronic equipment and the huge application market generated by it. Effective processing and understanding of human activities in data will have a profound impact on the development of human society. The purpose of sports human behavior analysis is to describe, recognize and understand human actions, human-human and human-environment interactions, which can be used in intelligent video survei...

AI Technical Summary

Problems solved by technology

Two-dimensional human body posture refers to a description of the distribution of human body joints on the two-dimensional plane of the image. The human body posture estimation of traditional two-dimensional images is greatly affected by surrounding environmental factors (clothes color, light) and occlusion. At the same time, there is a lack of pixel Spatial location information

Human body pose estimation based on deep convolutional neural network has obvious defects: it is only for RGB images, no depth data is used, and the network structure used by this method is very complicated (such as figure 2 ), the training efficiency is low

One is the method based on geodesic distance and optical flow represented by the method proposed by Loren Arthur Schwarz et al. The defect of this type of algorithm is that it is limited to the secondary skeleton points (elbow, knee, neck, shoulder, crotch). The positioning adopts the proportional positioning method, so the effect is not very ideal for people of different body types. At the same time, the application of optical flow requires a large amount of calculation and it is difficult to meet the occasions with high real-time requirements.

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