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Depth estimation from retinal disparity requires eye and head orientation signals

机译:从视网膜视差进行深度估计需要眼睛和头部方向信号

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摘要

To reach for an object, one needs to know its egocentric distance (absolute depth). It remains an unresolved issue which signals are required by the brain to calculate this absolute depth information. We devised a geometric model of binocular 3D eye orientation and investigated the signals necessary to uniquely determine the depth of a non-foveated object accounting for naturalistic variations of eye and head orientations. Our model shows that, in the presence of noisy internal estimates of the ocular vergence angle, horizontal and vertical retinal disparities alone are insufficient to calculate the unique depth of a point-like target. Instead the brain must account for the 3D orientations of the eye and head. We tested the model in a behavioral experiment that involved reaches to targets in depth. Our analysis showed that a target with the same retinal disparity produced different estimates of reach depth that varied consistently with different eye and head orientations. The experimental results showed that subjects accurately account for this extraretinal information when they reach. In summary, when estimating the distance of point-like targets, all available signals about the object`s location as well as body configuration are combined to provide accurate information about the object`s distance.
机译:为了到达一个物体,需要知道它的自我中心距离(绝对深度)。大脑需要哪些信号来计算此绝对深度信息仍未解决。我们设计了双眼3D眼睛定向的几何模型,并研究了唯一确定非凹入物体深度的必要信号,这些深度考虑了眼睛和头部定向的自然变化。我们的模型表明,在存在对眼发散角的嘈杂内部估计的情况下,仅水平和垂直视网膜视差就不足以计算点状目标的唯一深度。相反,大脑必须考虑到眼睛和头部的3D方向。我们在行为实验中测试了该模型,涉及到深入目标。我们的分析表明,具有相同视网膜差异的目标会产生不同的到达深度估计值,该估计值会随着眼睛和头部方向的不同而变化。实验结果表明,受试者到达时准确地解释了该视网膜外信息。总而言之,当估计点状目标的距离时,有关对象位置以及身体构造的所有可用信号都会组合在一起,以提供有关对象距离的准确信息。

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