Abstract
In this work, we propose an anthropometric dimensions measurement method based on 3D human model, namely Mesh2Measure. In our method, Human body features in the front and side images are firstly extracted and fused. And then, the feature vectors are attached to the template mesh model SMPL by using Graph-CNN, and 3D coordinates of the model vertices are regressed. Anthropometric dimensions of height, length, width and depth are calculated by scale conversion based on the model vertex coordinates. A novel general dense elliptic model is developed for the curve dimension or closed circumference dimension, which obtains human body dimensions by accumulating the length of elliptic segments with different coefficients. Data experiments are conducted by measuring 100 subjects. Experimental results show that our Mesh2Measure model can measure 38 main dimensions of human body in 15 s, and more importantly, the accuracy rate is 97.4% compared with the ground truth dimensions by manual measurements.
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Acknowledgments
This work was supported by National Natural Science Foundation of China (Grant Nos. 61873280, 61873281, 61972416), Taishan Scholarship (tsqn201812029), Major projects of the National Natural Science Foundation of China (Grant No. 41890851), Natural Science Foundation of Shandong Province (No. ZR2019MF012).
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Song, T., Zhang, R., Dong, Y., Tao, X., Lu, H., Liu, B. (2022). Mesh2Measure: A Novel Body Dimensions Measurement Based on 3D Human Model. In: Lv, Z., Song, H. (eds) Intelligent Technologies for Interactive Entertainment. INTETAIN 2021. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 429. Springer, Cham. https://doi.org/10.1007/978-3-030-99188-3_6
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