Yu Wurong, Xu Bugao
Department of Human Ecology, The University of Texas at Austin, Austin, TX 78712, USA.
Image Vis Comput. 2010 Apr 1;28(4):605-613. doi: 10.1016/j.imavis.2009.09.015.
This paper presents a whole body surface imaging system based on stereo vision technology. We have adopted a compact and economical configuration which involves only four stereo units to image the frontal and rear sides of the body. The success of the system depends on a stereo matching process that can effectively segment the body from the background in addition to recovering sufficient geometric details. For this purpose, we have developed a novel sub-pixel, dense stereo matching algorithm which includes two major phases. In the first phase, the foreground is accurately segmented with the help of a predefined virtual interface in the disparity space image, and a coarse disparity map is generated with block matching. In the second phase, local least squares matching is performed in combination with global optimization within a regularization framework, so as to ensure both accuracy and reliability. Our experimental results show that the system can realistically capture smooth and natural whole body shapes with high accuracy.
本文提出了一种基于立体视觉技术的全身表面成像系统。我们采用了一种紧凑且经济的配置，仅涉及四个立体单元来对身体的正面和背面进行成像。该系统的成功取决于立体匹配过程，该过程除了恢复足够的几何细节外，还能有效地将身体从背景中分割出来。为此，我们开发了一种新颖的亚像素密集立体匹配算法，该算法包括两个主要阶段。在第一阶段，借助视差空间图像中预定义的虚拟界面准确分割前景，并通过块匹配生成粗略的视差图。在第二阶段，在正则化框架内结合全局优化进行局部最小二乘匹配，以确保准确性和可靠性。我们的实验结果表明，该系统能够以高精度逼真地捕捉平滑自然的全身形状。
