Svarverud Ellen, Gilson Stuart J, Glennerster Andrew
School of Psychology and Clinical Language Sciences, University of Reading, Reading, UK.
J Vis. 2010 Jan 12;10(1):5.1-13. doi: 10.1167/10.1.5.
Cue combination rules have often been applied to the perception of surface shape but not to judgements of object location. Here, we used immersive virtual reality to explore the relationship between different cues to distance. Participants viewed a virtual scene and judged the change in distance of an object presented in two intervals, where the scene changed in size between intervals (by a factor of between 0.25 and 4). We measured thresholds for detecting a change in object distance when there were only 'physical' (stereo and motion parallax) or 'texture-based' cues (independent of the scale of the scene) and used these to predict biases in a distance matching task. Under a range of conditions, in which the viewing distance and position of the target relative to other objects was varied, the ratio of 'physical' to 'texture-based' thresholds was a good predictor of biases in the distance matching task. The cue combination approach, which successfully accounts for our data, relies on quite different principles from those underlying traditional models of 3D reconstruction.
线索组合规则常常被应用于表面形状的感知，但尚未应用于物体位置的判断。在此，我们利用沉浸式虚拟现实技术来探究不同距离线索之间的关系。参与者观看一个虚拟场景，并判断在两个时间间隔内呈现的物体的距离变化，其中场景在两个时间间隔之间大小发生变化（变化系数在0.25至4之间）。当只有“物理”（立体视觉和运动视差）或“基于纹理”的线索（与场景比例无关）时，我们测量了检测物体距离变化的阈值，并利用这些阈值来预测距离匹配任务中的偏差。在一系列条件下，其中观察距离以及目标相对于其他物体的位置有所变化，“物理”线索与“基于纹理”线索的阈值之比能够很好地预测距离匹配任务中的偏差。成功解释我们数据的线索组合方法所依赖的原理与传统三维重建模型所依据的原理截然不同。
