用两台RGB-D相机实现人体各部位体积精确估算
Human Body Segment Volume Estimation with Two RGB-D Cameras
- 基于双相机与改进的非刚性配准算法重建三维身体模型
- 在FAUST数据集上精度接近激光扫描,尤其改善了侧面间隙处的几何一致性
- 适合临床评估肢体体积比,助力健康监测与人体工学设计
在人体测量学中,准确估算全身及各肢体段体积具有重要意义,可支持健康评估、人因工程优化和生物力学模型定制。本文提出一种仅使用两台RGB-D相机的体部段体积估算(BSV)系统。为提升精度以媲美3D激光扫描,我们改进了As-Rigid-As-Possible(ARAP)非刚性配准方法,将能量函数从单一三角网格解耦,显著提升了重建网格在侧向空隙区域的几何一致性。通过分析相机性能、在FAUST数据集上的结果,并与现有先进方法对比,最终在真实采集中验证了该系统在人体体积估计方面的优越性,能够有效评估近端与远端肢体段的体积比,该指标在多种临床应用中具有重要价值。
原文摘要 · Abstract (English)
In the field of human biometry, accurately estimating the volume of the whole body and its individual segments is of fundamental importance. Such measurements support a wide range of applications that include assessing health, optimizing ergonomic design, and customizing biomechanical models. In this work, we presented a Body Segment Volume Estimation (BSV) system to automatically compute whole-body and segment volumes using only two RGB-D cameras, thus limiting the system complexity. However, to maintain the accuracy comparable to 3D laser scanners, we enhanced the As-Rigid-As-Possible (ARAP) non-rigid registration techniques, disconnecting its energy from the single triangle mesh. Thus, we improved the geometrical coherence of the reconstructed mesh, especially in the lateral gap areas. We evaluated BSV starting from the RGB-D camera performances, through the results obtained with FAUST dataset human body models, and comparing with a state-of-the-art work, up to real acquisitions. It showed superior ability in accurately estimating human body volumes, and it allows evaluating volume ratios between proximal and distal body segments, which are useful indices in many clinical applications.
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