人类和人工视觉系统共享一个计算原理,用于将双眼差异转化为深度表示
Bayu Gautama Wundari1, Ichiro Fujita1,2,3,4, Hiroshi Ban5,6
1Graduate School of Frontier Biosciences, Osaka University, Suita, Japan.
Communications biology
|July 11, 2025
概括
人类大脑对深度感知进行双眼差异处理,早期视觉区域 (V1-V3) 使用交叉相关性,后期区域 (V3A/B,V7,hV4,hMT+) 使用交叉匹配. 这反映了用于3D视觉的深度神经网络 (DNN) 计算.
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
- 人类视觉皮层视觉皮层
背景情况:
- 视觉大脑解读双眼差异来感知深度.
- 早期视觉皮层神经元 (V1) 使用交叉相关性,对匹配和不匹配的图像特征作出反应,创建一个模两可的深度表示.
- 这种表示通过在后面的视觉区域进行非线性交叉匹配计算来完善,以过不匹配.
研究的目的:
- 研究人类视觉皮层中深度表示的组织.
- 将人类立体视觉的计算原理与深度神经网络 (DNN) 的计算原理进行比较.
主要方法:
- 功能磁共振成像 (fMRI) 用于绘制大脑活动的地图.
- 为了进行比较,分析了一种训练用于立体视觉的深度神经网络 (DNN).
主要成果:
- V1-V3区域显示出更强的交叉相关成分,这是初始差异处理的特征.
- 区域V3A/B,V7,hV4和hMT+显示了向交叉匹配计算的转变,表明了精细的深度处理.
- DNN表现出类似的分层转换,从交叉相关性向交叉匹配原则发展.
结论:
- 人类视觉皮层表现出深度感知的层次组织,从交叉相关性过渡到交叉匹配计算.
- 该研究揭示了人类和人工视觉系统之间的共享计算原则,以实现强大的3D视觉.
- 这种大脑-DNN对齐为立体视觉的神经基础提供了洞察力.
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