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.
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Acknowledgements
On the digitalized 3D model of Tibetan Xianziwu based on 3D Motion Capture (Innovation-Supportive Project for Young Teachers in Colleges and Universities in Tibet Autonomous Region) QCZ2016—33.
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© 2019 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
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Liu, Zg. (2019). Human Motion Attitude Tracking Method Based on Vicon Motion Capture Under Big Data. In: Gui, G., Yun, L. (eds) Advanced Hybrid Information Processing. ADHIP 2019. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 301. Springer, Cham. https://doi.org/10.1007/978-3-030-36402-1_41
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DOI: https://doi.org/10.1007/978-3-030-36402-1_41
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