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Erschienen in:
2019 | OriginalPaper | Buchkapitel
Human Motion Attitude Tracking Method Based on Vicon Motion Capture Under Big Data
verfasst von : Ze-guo Liu
Erschienen in: Advanced Hybrid Information Processing
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Abstract
Aiming at the problem that the human body motion posture cannot be correctly and quickly marked in the conventional method, a human body motion attitude tracking method based on Vicon motion capture under big data is proposed and designed. Under the motion capture filtering algorithm, the human body weight measurement function is constructed by the combination of color, edge and motion features, and different images are selected according to the occlusion between limbs to establish a constrained human motion model, and the model is based on Vicon action. The tracking calculation of the capture realizes the tracking process of the human body motion posture. The effectiveness of the method is determined by the method of experimental argumentation analysis. The results show that the method can track the motion posture of the human body quickly and accurately, and the robustness is better. The tracking accuracy is 13.87% higher than the conventional method.