Graduate School of Informatics, Kansai University, USA.
Percept Mot Skills. 2011 Aug;113(1):113-26. doi: 10.2466/03.24.27.PMS.113.4.113-126.
Visible surfaces of three-dimensional objects are reconstructed from two-dimensional retinal images in the early stages of human visual processing. In the computational model of surface reconstruction based on the standard regularization theory, an energy function is minimized. Two types of model have been proposed, called "membrane" and "thin-plate" after their function formulas, in which the first or the second derivative of depth information is used. In this study, the threshold of surface reconstruction from binocular disparity was investigated using a sparse random dot stereogram, and the predictive accuracy of these models was evaluated. It was found that the thin-plate model reconstructed surfaces more accurately than the membrane model and showed good agreement with experimental results. The likelihood that these models imitate human processing of visual information is discussed in terms of the size of receptive fields in the visual pathways of the human cortex.
在人类视觉处理的早期阶段，从二维视网膜图像中重建三维物体的可见表面。在基于标准正则化理论的表面重建计算模型中，最小化一个能量函数。根据其函数公式，提出了两种类型的模型，分别称为“膜”和“薄板”，其中使用了深度信息的一阶或二阶导数。在这项研究中，使用稀疏随机点立体图研究了从双目视差重建表面的阈值，并评估了这些模型的预测准确性。结果发现，薄板模型比膜模型重建的表面更准确，并且与实验结果吻合较好。根据人类大脑皮层视觉通路的感受野大小，讨论了这些模型模拟人类视觉信息处理的可能性。
