解析视觉感受野与图像仿射变换的自由度关系,揭示大脑如何适应视角变化。
Relationships between the degrees of freedom in the affine Gaussian derivative model for visual receptive fields and 2-D affine image transformations, with application to covariance properties of simple cells in the primary visual cortex
- 用可分解的仿射变换模型,拆解图像变形的四类自由度。
- 发现神经感受野的参数自由度与图像变换自由度匹配。
- 为视觉皮层处理视角变化提供理论支持,适合神经科学与计算机视觉研究者。
观察由光滑曲面构成的物体表面图案时,其在图像域中的投影会因几何观测条件的变化而产生显著差异,这些差异由单眼或双眼成像条件或物体与观察者之间的相对运动引起。一阶近似下,这类图像形变可建模为局部二维空间仿射变换的线性化形式。本文对二维空间仿射图像变换的自由度与视觉感受野的仿射高斯导数模型的自由度之间的关系进行了理论分析。首先,提出一种基于乘积形式的二维仿射变换规范分解,类似于奇异值分解,且具有闭式表达,揭示了四类自由度:(i) 均匀缩放,(ii) 总体全局旋转,(iii) 补充的非均匀缩放,(iv) 相对于图像域中偏好对称方向的相对归一化。随后,展示这些自由度如何对应于仿射高斯导数模型的自由度。最后,利用这些理论结果,结合现有神经生理学实验数据,探讨高等哺乳动物初级视觉皮层中的生物感受野是否能覆盖二维空间仿射变换的所有自由度。
原文摘要 · Abstract (English)
When observing the surface patterns of objects delimited by smooth surfaces, the projections of the surface patterns to the image domain will be subject to substantial variabilities, as induced by variabilities in the geometric viewing conditions, and as generated by either monocular or binocular imaging conditions, or by relative motions between the object and the observer over time. To first order of approximation, the image deformations of such projected surface patterns can be modelled as local linearizations in terms of local 2-D spatial affine transformations. This paper presents a theoretical analysis of relationships between the degrees of freedom in 2-D spatial affine image transformations and the degrees of freedom in the affine Gaussian derivative model for visual receptive fields. For this purpose, we first describe a canonical decomposition of 2-D affine transformations on a product form, closely related to a singular value decomposition, while in closed form, and which reveals the degrees of freedom in terms of (i) uniform scaling transformations, (ii) an overall amount of global rotation, (iii) a complementary non-uniform scaling transformation and (iv) a relative normalization to a preferred symmetry orientation in the image domain. Then, we show how these degrees of freedom relate to the degrees of freedom in the affine Gaussian derivative model. Finally, we use these theoretical results to consider whether we could regard the biological receptive fields in the primary visual cortex of higher mammals as being able to span the degrees of freedom of 2-D spatial affine transformations, based on interpretations of existing neurophysiological experimental results.
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