Estimation of Center of Mass for Sports Scene Using Weighted Visual Hull

Tomoya Kaichi, Shohei Mori, Hideo Saito, Kosuke Takahashi, Dan Mikami, Mariko Isogawa, Hideaki Kimata; The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2018, pp. 1809-1815

Abstract


This paper presents a method to estimate the 3D position of a center of mass (CoM) of a human body from a set of multi-view images. As a well-known fact, in sports, collections of CoM are important for analyzing the athletes' performance. Most conventional studies in CoM estimation require installing a measuring system (e.g., a force plate or optical motion capture system) or attaching sensors to the athlete. While such systems reliably estimate CoM, casual settings are preferable for simplifying preparations. To address this issue, the proposed method takes a vision-based approach that does not require specialized hardware and wearable devices. Our method calculates subject's CoM using voxels with body parts dependent weighting. This individual voxel reconstruction and voxel-wise weighting reflects the differences in each body shape, and are expected to contribute to higher performance in analysis. The results using real data demonstrated the performance of the proposed method were compared to force plate data, and provided a 3D CoM visualization in a dynamic scene.

Related Material


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[bibtex]
@InProceedings{Kaichi_2018_CVPR_Workshops,
author = {Kaichi, Tomoya and Mori, Shohei and Saito, Hideo and Takahashi, Kosuke and Mikami, Dan and Isogawa, Mariko and Kimata, Hideaki},
title = {Estimation of Center of Mass for Sports Scene Using Weighted Visual Hull},
booktitle = {The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
month = {June},
year = {2018}
}