一个贝叶斯模型的距离感知从眼睛收的贝叶斯模型
Peter Scarfe1, Paul B Hibbard2
1Vision and Haptics Laboratory, School of Psychology and Clinical Language Sciences, University of Reading, Reading, United Kingdom.
PLoS computational biology
|October 3, 2025
概括
人类低估了物体距离,原因是的眼收信号. 一个概率模型通过视觉系统推断出最可能的距离从不完美的接数据来解释这种偏差.
科学领域:
- 视觉神经科学 视觉神经科学
- 感知科学是感知科学.
- 计算建模计算建模
背景情况:
- 眼睛的收是绝对距离感知的一个关键提示.
- 人类系统地低估了物体距离,特别是对于更远的物体.
- 这种低估距离挑战了接作为线索的可靠性.
研究的目的:
- 为了解释系统地低估距离,尽管眼睛的准确收.
- 为距离感知提出一个概率几何模型.
- 为了研究噪声在源信号中的作用.
主要方法:
- 开发了一个概率几何模型.
- 模拟视觉系统对最可能的距离的估计,基于杂的融合信号.
- 制定了一个概率函数,考虑距离和收之间的生成关系.
主要成果:
- 该模型成功地解释了人类对距离的低估.
- 交汇信号中所需的噪声水平与实验测量结果一致.
- 概率函数的制定对于解释观察到的偏差至关重要.
结论:
- 低估距离是视觉系统从杂的感觉数据中推断概率的结果.
- 融合仍然是一个可行的,虽然杂的,绝对距离感知的提示.
- 这项研究强调了生成模型在理解感知偏差方面的重要性.
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