作为因果推理的等级运动感知
Sabyasachi Shivkumar1,2, Gregory C DeAngelis1,3, Ralf M Haefner1,3
1Brain and Cognitive Sciences, University of Rochester, Rochester, NY 14627, USA.
bioRxiv : the preprint server for biology
|November 28, 2023
概括
运动的感知依赖于理解参考框架. 一个新的贝叶斯模型解释了大脑如何通过整合多个层次组织的参考框架中的视觉信息来推断感知运动.
科学领域:
- 认知神经科学 认知神经科学
- 计算视觉 计算机视觉 计算机视觉
- 心理物理学的精神物理.
背景情况:
- 定义运动感知是具有挑战性的,因为参考框架的相对性.
- 之前的心理物理研究产生了关于主导参考框架 (视网膜,自我中心,以世界为中心,以对象为中心) 的相互矛盾的证据.
研究的目的:
- 介绍一个层次化的贝叶斯模型,解释视网膜速度是如何映射到感知速度的.
- 调查多个因果相关的参考框架在视觉运动感知中的作用.
- 为理解感知中的参考框架选择提供规范框架.
主要方法:
- 开发了一个层次化的贝叶斯模型,在参考框架内表示静止速度之前包含一个"摩擦".
- 倒置模型以展示视觉输入的自动细分成等级组和在适当的框架内"感知"运动.
- 进行了两项新的实验,以测试关键模型预测.
主要成果:
- 该模型通过考虑参考框架的层次结构,成功地将视网膜速度映射到感知速度.
- 模型倒置证明了视觉场景的自动细分和在相关内识别运动.
- 实验数据支持等级贝叶斯模型的关键预测.
- 推断出个别观察者的主观参考框架集.
结论:
- 提出的等级贝叶斯模型为理解运动感知中的参考框架选择提供了一个统一的框架.
- 该模型为基本的格斯塔尔特原则提供了定量,规范的理由.
- 这项工作激发了对视觉处理的更复杂模型的开发.
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