Image-based center of mass estimation of the human body via 3D shape and kinematic structure

Abstract

This paper presents a method to estimate a time-sequential trajectory of the center of mass (CoM) of an athlete from a multi-view set of cameras. Collecting the CoM typically requires large-scale measuring systems or attaching sensors to the athletes. To mitigate such hardware limitations, the present study takes a multi-view video-based approach. The proposed method reconstructs subjects’ voxels from a set of multi-view frames and weights each voxel with body part-dependent weights to calculate a CoM. Our results, using real data measured in a studio, showed that the proposed method can estimate CoM within 20 mm concerning center of pressure measures.

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    https://www.gimp.org/.

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    https://www.xsens.com/products/xsens-mvn-analyze/.

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Acknowledgements

This work was supported by Grant-in-Aid for JSPS Fellows (19J22153).

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Correspondence to Tomoya Kaichi.

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Kaichi, T., Mori, S., Saito, H. et al. Image-based center of mass estimation of the human body via 3D shape and kinematic structure. Sports Eng 22, 17 (2019). https://doi.org/10.1007/s12283-019-0309-2

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Keywords

  • Center of mass
  • Multi-view videos
  • Visual hull
  • Multi-view human pose estimation