灵活计算物体运动和深度,基于从光流中推断出的视觉几何学
Zhe-Xin Xu1,2, Jiayi Pang1,3, Akiyuki Anzai1
1Department of Brain and Cognitive Sciences, Center for Visual Science, University of Rochester, Rochester, NY, USA.
bioRxiv : the preprint server for biology
|June 6, 2025
概括
大脑根据推断的视觉几何学自动调整视觉感知,即使没有物理眼睛运动. 这种适应过程对于在动态3D环境中准确感知物体运动和深度至关重要.
科学领域:
- 神经科学是一个神经科学.
- 计算视觉 计算机视觉 计算机视觉
- 感知 感知 感知 感知
背景情况:
- 视觉是一个活跃的过程,涉及眼睛和头部的运动.
- 视网膜图像运动分析因自我运动而复杂化.
- 目前存在的眼动补偿模型在复杂的视觉几何形状下失败.
研究的目的:
- 为了研究大脑如何在视觉感知过程中解释自我运动.
- 根据推断的观测几何学,开发对物体运动和深度感知的理论预测.
- 探索适应视觉计算的神经基础.
主要方法:
- 开发了对物体运动和深度感知的理论预测.
- 进行心理物理实验,模拟使用光流的视觉几何形状.
- 使用神经网络模型训练在类似的任务.
主要成果:
- 在没有物理眼睛运动的情况下,表现出新的感知偏见.
- 表明这些偏差是由理论框架预测的,并自动发生.
- 神经网络模型表现出类似于地区MT的响应模式.
结论:
- 视觉系统自动从光流中推断出视觉几何.
- 图像运动组件灵活地归因于自我运动或场景结构.
- 自动运动感知对于计算动态3D环境中的物体运动和深度至关重要.
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