Rosas Pedro, Wichmann Felix A, Wagemans Johan
Department of Psychology, University of Leuven, Tiensestraat 102, B-3000 Leuven, Belgium.
Vision Res. 2004;44(13):1511-35. doi: 10.1016/j.visres.2004.01.013.
We measure the performance of five subjects in a two-alternative-forced-choice slant-discrimination task for differently textured planes. As textures we used uniform lattices, randomly displaced lattices, circles (polka dots), Voronoi tessellations, plaids, 1/f noise, "coherent" noise and a leopard skin-like texture. Our results show: (1) Improving performance with larger slants for all textures, (2) and some cases of "non-symmetrical" performance around a particular orientation. (3) For orientations sufficiently slanted, the different textures do not elicit major differences in performance, (4) while for orientations closer to the vertical plane there are marked differences among them. (5) These differences allow a rank-order of textures to be formed according to their "helpfulness"--that is, how easy the discrimination task is when a particular texture is mapped on the plane. Polka dots tend to allow the best slant discrimination performance, noise patterns the worst. Two additional experiments were conducted to test the generality of the obtained rank-order. First, the tilt of the planes was rotated by 90 degrees. Second, the task was changed to a slant report task via probe adjustment. The results of both control experiments confirmed the texture rank-order previously obtained. We then test a number of spatial-frequency-based slant-from-texture models and discuss their shortcomings in explaining our rank-order. Finally, we comment on the importance of these results for depth-perception research in general, and in particular the implications our results have for studies of cue combination (sensor fusion) using texture as one of the cues involved.
我们测量了五名受试者在针对不同纹理平面的二选一强制选择倾斜辨别任务中的表现。作为纹理,我们使用了均匀晶格、随机位移晶格、圆形(圆点)、沃罗诺伊镶嵌、格子图案、1/f噪声、“相干”噪声以及豹皮状纹理。我们的结果表明:(1)对于所有纹理,倾斜度越大表现越好;(2)在特定方向周围存在一些“非对称”表现的情况;(3)对于倾斜度足够大的方向,不同纹理在表现上没有显著差异;(4)而对于更接近垂直平面的方向,它们之间存在明显差异;(5)这些差异使得可以根据纹理的“帮助程度”形成一个排序——也就是说,当特定纹理映射到平面上时,辨别任务的难易程度。圆点往往能带来最佳的倾斜辨别表现,噪声图案则最差。我们进行了另外两个实验来检验所得到排序的普遍性。首先,将平面的倾斜度旋转90度。其次,通过探针调整将任务改为倾斜报告任务。两个对照实验的结果都证实了之前得到的纹理排序。然后我们测试了一些基于空间频率的从纹理感知倾斜模型,并讨论了它们在解释我们的排序时的不足之处。最后,我们总体评论了这些结果对于深度感知研究的重要性,特别是我们的结果对于使用纹理作为其中一个线索的线索组合(传感器融合)研究的意义。