Human shape reconstruction via graph cuts for voxel-based markerless motion capture in intelligent environment

M. Shimosaka, Kazuhiko Murasaki, Taketoshi Mori, Tomomasa Sato
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引用次数: 2

Abstract

In this paper, we propose a robust and real-time 3D human shape reconstruction method in daily life spaces to make practical voxel-based motion capture systems. Our algorithm extracts human silhouette and reconstructs human shape via volume intersection from multi view point images. The method presented in this paper is based on energy minimization via graph cuts, and its main features are: 1) to reduce the background subtraction errors caused by background clutter, 2) to have robustness for influences of shadows, 3) to segment the foreground region even if moving objects other than human. The precise human shape reconstructed by the method improves the accuracy of human pose estimation. Especially, 3) leads to enhance the range of application of the voxel-based human pose estimation. We demonstrate the effectiveness of our approach in terms of both quantitative and qualitative performance where strong shadows appear and moving objects are present in intelligent environment.
智能环境下基于体素的无标记运动捕捉的图形切割人体形状重建
在本文中,我们提出了一种在日常生活空间中鲁棒和实时的三维人体形状重建方法,以实现实用的基于体素的运动捕捉系统。该算法从多视点图像中提取人体轮廓,并通过体交重建人体形状。本文提出的方法基于图切割能量最小化,其主要特点是:1)减少背景杂波引起的背景减除误差;2)对阴影的影响具有鲁棒性;3)即使是非人的运动物体也能分割前景区域。通过该方法重建的精确人体形状提高了人体姿态估计的精度。特别是3)增强了基于体素的人体姿态估计的应用范围。我们在智能环境中出现强烈阴影和移动物体的定量和定性性能方面证明了我们的方法的有效性。
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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