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

Tomoya Kaichi, Shohei Mori, H. Saito, Kosuke Takahashi, Dan Mikami, Mariko Isogawa, H. Kimata
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引用次数: 9

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.
基于加权视觉船体的运动场景质心估计
本文提出了一种从多视图图像中估计人体质心的三维位置的方法。作为一个众所周知的事实,在体育运动中,CoM的集合对于分析运动员的表现非常重要。大多数传统的CoM估计研究需要安装测量系统(例如,测力板或光学运动捕捉系统)或在运动员身上安装传感器。虽然这种系统可靠地估计CoM,但为了简化准备工作,更可取的是临时设置。为了解决这个问题,提出的方法采用基于视觉的方法,不需要专门的硬件和可穿戴设备。我们的方法使用体素与身体部位相关的加权来计算受试者的CoM。这种单独的体素重建和体素加权反映了每个身体形状的差异,并有望有助于提高分析的性能。实际数据验证了该方法的有效性,并与力板数据进行了比较,为动态场景下的三维CoM可视化提供了依据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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