Prince S J, Eagle R A
University Laboratory of Physiology, University of Oxford, South Parks Road, Oxford, UK.
Vision Res. 2000;40(9):1143-55. doi: 10.1016/s0042-6989(99)00241-2.
Previous work [Prince, S. J. D, & Eagle, R. A. (1999). Size-disparity correlation in human binocular depth perception. Proceedings of the Royal Society: Biological Sciences, 266, 1361-1365] has demonstrated that disparity sign discrimination performance in isolated bandpass patterns is supported at disparities much larger than a phase disparity model might predict. One possibility is that this extended performance relies on a separate second-order system [Hess, R. F., & Wilcox, L. M. (1994). Linear and non-linear filtering in stereopsis. Vision Research, 34, 2431-2438]. Here, a 'weighted directional energy' model is developed which explains a large body of crossed versus uncrossed disparity discrimination data with a single mechanism. This model assumes a population of binocular complex cells at every image point with a range of position disparity shifts. These cells sample a local energy function which is weighted so that energy at large disparities is relatively attenuated. Disparity sign is determined by summing and comparing energy at crossed and uncrossed disparities in the presence of noise. The model qualitatively predicts matching data for one-dimensional Gabor stimuli. This scheme also predicts DMax in Gabor stimuli and filtered noise. Moreover, a range of 'non-linear' phenomena, in which disparity is perceived from contrast envelope information alone, can be explained. The weighted directional energy model presents a biologically plausible, parsimonious explanation of matching behaviour in bandpass stimuli for both 'first-order' and 'second-order' stimuli which obviates the need for multiple mechanisms in stereo correspondence.
先前的研究[普林斯，S. J. D，& 伊格尔，R. A.（1999年）。人类双眼深度感知中的大小差异相关性。《皇家学会学报：生物科学》，266，1361 - 1365]表明，在孤立的带通图案中，视差符号辨别性能在比相位视差模型预测的大得多的视差下得到支持。一种可能性是，这种扩展性能依赖于一个单独的二阶系统[赫斯，R. F.，& 威尔科克斯，L. M.（1994年）。立体视觉中的线性和非线性滤波。《视觉研究》，34，2431 - 2438]。在此，开发了一种“加权方向能量”模型，该模型用单一机制解释了大量交叉与非交叉视差辨别数据。该模型假设在每个图像点存在一群具有一系列位置视差偏移的双眼复杂细胞。这些细胞对局部能量函数进行采样，该能量函数被加权，使得大视差处的能量相对衰减。视差符号通过在有噪声的情况下对交叉和非交叉视差处的能量求和并比较来确定。该模型定性地预测了一维伽柏刺激的匹配数据。该方案还预测了伽柏刺激和滤波噪声中的最大可分辨视差（DMax）。此外，一系列仅从对比度包络信息就能感知视差的“非线性”现象也可以得到解释。加权方向能量模型为带通刺激中“一阶”和“二阶”刺激的匹配行为提供了一种生物学上合理、简洁的解释，从而无需在立体匹配中使用多种机制。
