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A computational theory of visual receptive fields

机译:视觉感受域的计算理论

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摘要

A receptive field constitutes a region in the visual field where a visual cell or a visual operator responds to visual stimuli. This paper presents a theory for what types of receptive field profiles can be regarded as natural for an idealized vision system, given a set of structural requirements on the first stages of visual processing that reflect symmetry properties of the surrounding world. These symmetry properties include (i) covariance properties under scale changes, affine image deformations, and Galilean transformations of space–time as occur for real-world image data as well as specific requirements of (ii) temporal causality implying that the future cannot be accessed and (iii) a time-recursive updating mechanism of a limited temporal buffer of the past as is necessary for a genuine real-time system. Fundamental structural requirements are also imposed to ensure (iv) mutual consistency and a proper handling of internal representations at different spatial and temporal scales. It is shown how a set of families of idealized receptive field profiles can be derived by necessity regarding spatial, spatio-chromatic, and spatio-temporal receptive fields in terms of Gaussian kernels, Gaussian derivatives, or closely related operators. Such image filters have been successfully used as a basis for expressing a large number of visual operations in computer vision, regarding feature detection, feature classification, motion estimation, object recognition, spatio-temporal recognition, and shape estimation. Hence, the associated so-called scale-space theory constitutes a both theoretically well-founded and general framework for expressing visual operations. There are very close similarities between receptive field profiles predicted from this scale-space theory and receptive field profiles found by cell recordings in biological vision. Among the family of receptive field profiles derived by necessity from the assumptions, idealized models with very good qualitative agreement are obtained for (i) spatial on-center/off-surround and off-center/on-surround receptive fields in the fovea and the LGN, (ii) simple cells with spatial directional preference in V1, (iii) spatio-chromatic double-opponent neurons in V1, (iv) space–time separable spatio-temporal receptive fields in the LGN and V1, and (v) non-separable space–time tilted receptive fields in V1, all within the same unified theory. In addition, the paper presents a more general framework for relating and interpreting these receptive fields conceptually and possibly predicting new receptive field profiles as well as for pre-wiring covariance under scaling, affine, and Galilean transformations into the representations of visual stimuli. This paper describes the basic structure of the necessity results concerning receptive field profiles regarding the mathematical foundation of the theory and outlines how the proposed theory could be used in further studies and modelling of biological vision. It is also shown how receptive field responses can be interpreted physically, as the superposition of relative variations of surface structure and illumination variations, given a logarithmic brightness scale, and how receptive field measurements will be invariant under multiplicative illumination variations and exposure control mechanisms.
机译:感受野构成了视野中视觉细胞或视觉操作者对视觉刺激作出反应的区域。本文提出了一种理论,即对于理想化的视觉系统而言,哪种类型的感受野剖面可以被认为是自然的,前提是视觉处理的第一阶段具有一组结构要求,这些要求反映了周围世界的对称特性。这些对称属性包括(i)比例变化,仿射图像变形和时空的伽利略变换在真实世界图像数据中发生的协方差属性,以及(ii)时间因果关系的特定要求,这意味着无法访问未来(iii)过去的有限时间缓冲区的时间递归更新机制,这对于真正的实时系统而言是必需的。还提出了基本的结构要求,以确保(iv)在不同的时空尺度上相互一致并正确处理内部表示形式。它显示了如何根据高斯核,高斯导数或紧密相关的算子,根据空间,时空色度和时空接受域的必要性,可以导出一组理想化的接受域轮廓。此类图像滤镜已成功用作表达计算机视觉中大量视觉操作的基础,涉及特征检测,特征分类,运动估计,物体识别,时空识别和形状估计。因此,相关的所谓的尺度空间理论构成了表达视觉操作的理论基础和通用框架。根据这种尺度空间理论预测的感受野概况与生物视觉中细胞记录发现的感受野概况之间存在非常相似的相似之处。在从假设必要性推导出的一系列接收场剖面中,针对(i)中央凹和中心凹的空间中心/偏心周围和偏心/周围周围感受野获得了具有很好定性一致性的理想模型LGN,(ii)V1中具有空间方向偏好的简单细胞,(iii)V1中的时空色双对手神经元,(iv)LGN和V1中的时空可分时空时空接受场,(v)非V1中可分离的时空倾斜接收场,都在同一统一理论中。此外,本文提出了一个更一般的框架,用于从概念上关联和解释这些接受域,并可能预测新的接受域概况,以及在缩放,仿射和伽利略变换成视觉刺激表示形式之前进行预接线协方差。本文描述了有关接受场剖面的必要结果的基本结构,这是该理论的数学基础,并概述了所提出的理论如何用于生物视觉的进一步研究和建模。还显示了在给定对数亮度标度的情况下,如何物理地将感受野响应解释为表面结构和光照变化的相对变化的叠加,以及在成倍的光照变化和曝光控制机制下感受野的测量将如何不变。

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    Lindeberg, Tony;

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  • 年度 2013
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  • 原文格式 PDF
  • 正文语种 eng
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