We assessed the contribution of binocular disparity and the pictorial cues of linear perspective, texture, and scene clutter to the perception of distance in consumer virtual reality. As additional cues are made available, distance perception is predicted to improve, as measured by a reduction in systematic bias, and an increase in precision. We assessed (1) whether space is nonlinearly distorted; (2) the degree of size constancy across changes in distance; and (3) the weighting of pictorial versus binocular cues in VR. In the first task, participants positioned two spheres so as to divide the egocentric distance to a reference stimulus (presented between 3 and 11 m) into three equal thirds. In the second and third tasks, participants set the size of a sphere, presented at the same distances and at eye-height, to match that of a hand-held football. Each task was performed in four environments varying in the available cues. We measured accuracy by identifying systematic biases in responses and precision as the standard deviation of these responses. While there was no evidence of nonlinear compression of space, participants did tend to underestimate distance linearly, but this bias was reduced with the addition of each cue. The addition of binocular cues, when rich pictorial cues were already available, reduced both the bias and variability of estimates. These results show that linear perspective and binocular cues, in particular, improve the accuracy and precision of distance estimates in virtual reality across a range of distances typical of many indoor environments.

我们评估了双目视差以及线性透视，纹理和场景混乱的图形提示对消费者虚拟现实中距离感知的贡献。随着其他提示的出现，通过减少系统偏差和提高精度可以预测距离感知会改善。我们评估（1）空间是否非线性失真；（2）距离变化中的尺寸一致性程度；（3）虚拟实境中图片提示与双目提示的权重。在第一个任务中，参与者将两个球体定位成将以自我为中心的距离与参考刺激（在3至11 m之间）划分为三个相等的三分之二。在第二和第三项任务中，参与者设置球体的大小，以相同的距离和眼睛的高度显示，以匹配手持式足球的大小。每个任务都是在四个可用提示不同的环境中执行的。我们通过识别响应中的系统偏差和精度作为这些响应的标准偏差来测量准确性。尽管没有证据表明空间存在非线性压缩，但参与者确实倾向于线性低估距离，但是随着每个提示的加入，这种偏见得以减少。当已经有了丰富的图形提示时，增加双目提示就可以减少估计的偏差和可变性。这些结果表明，线性透视和双目线索尤其可以提高虚拟现实中跨许多室内环境的典型距离范围的距离估计的准确性和精确度。我们通过识别响应中的系统偏差和精度作为这些响应的标准偏差来测量准确性。尽管没有证据表明空间存在非线性压缩，但参与者确实倾向于线性低估距离，但是随着每个提示的加入，这种偏见得以减少。当已经有了丰富的图形提示时，增加双目提示就可以减少估计的偏差和可变性。这些结果表明，线性透视和双目线索尤其可以提高虚拟现实中跨许多室内环境的典型距离范围的距离估计的准确性和精确度。我们通过识别响应中的系统偏差和精度作为这些响应的标准偏差来测量准确性。尽管没有证据表明空间存在非线性压缩，但参与者确实倾向于线性低估距离，但是随着每个提示的加入，这种偏见得以减少。当已经有了丰富的图形提示时，增加双目提示就可以减少估计的偏差和可变性。这些结果表明，线性透视和双目线索尤其可以提高虚拟现实中跨许多室内环境的典型距离范围的距离估计的准确性和精确度。但是随着每个提示的加入，这种偏见得以减少。当已经有了丰富的图形提示时，增加双目提示就可以减少估计的偏差和可变性。这些结果表明，线性透视和双目线索尤其可以提高虚拟现实中跨许多室内环境的典型距离范围的距离估计的准确性和精确度。但是随着每个提示的加入，这种偏见得以减少。当已经有了丰富的图形提示时，增加双目提示就可以减少估计的偏差和可变性。这些结果表明，线性透视和双目线索尤其可以提高虚拟现实中跨许多室内环境的典型距离范围的距离估计的准确性和精确度。