Do humans optimally integrate stereo and texture information for judgments of surface slant?
Do humans optimally integrate stereo and texture information for judgments of surface slant?
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DOI：
10.1016/s0042-6989(03)00458-9
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发表时间：
2003-11-01
期刊：
影响因子：
1.8
通讯作者：
Saunders, JA
中科院分区：
文献类型：
--
作者：
Knill, DC;Saunders, JA
将视觉线索与三维表面几何图形相结合的最优线性系统，其权重与线索的不确定性成反比。结合纹理和立体信息进行平面倾斜判断的问题为人类感知的最优性提供了强有力的检验。由于纹理判断的斜度准确度从低斜度到高斜度会有一个数量级的变化，因此最优性预测了线索权重作为表面斜度的函数的相应变化。此外，由于人类在使用纹理和立体信息判断3D表面几何形状的能力上表现出显著的个体差异，因此该问题允许更强的测试，即受试者从个体线索中区分倾斜的阈值的个体差异应该预测线索权重的个体差异。我们通过测量倾斜辨别阈值和立体/纹理线索权重作为多受试者表面倾斜的函数来测试这两种预测。结果证实了两种最优性的预测，除了纹理信息的明显轻微加权不足。这可能是由实验中用于分离立体信息的刺激的特定因素造成的。综上所述，结果与人类最优地将两种线索结合到表面倾斜的假设一致，线索权重与线索的主观可靠性成正比。(C) 2003 Elsevier Ltd.版权所有。
An optimal linear system for integrating Visual cues to 3D surface geometry weights Cues ill inverse proportion to their uncertainty. The problem of integrating texture and stereo information for judgments of planar surface slant provides a strong test of optimality in human perception. Since the accuracy of slant from texture judgments changes by an order of magnitude from low to high slants, optimality predicts corresponding changes in cue weights as a function Of Surface slant. Furthermore, Since humans show significant individual differences in their abilities to use both texture and stereo information for judgments of 3D Surface geometry, the problem admits the stronger test that individual differences in subjects' thresholds for discriminating slant from the individual cues should predict individual differences in cue weights. We tested both predictions by measuring slant discrimination thresholds and stereo/texture cue weights as a function of surface slant for multiple subjects. The results bear Out both predictions of optimality, with the exception of an apparent slight under-weighting Of texture information. This may be accounted for by factors specific to the Stimuli used to isolate stereo information in the experiments. Taken together, the results are consistent with the hypothesis that humans optimally combine the two cues to surface slant, with Cue weights proportional to the subjective reliability of the cues. (C) 2003 Elsevier Ltd. All rights reserved.