当前位置:
X-MOL 学术
›
arXiv.cs.CY
›
论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
A Linked Aggregate Code for Processing Faces (Revised Version)
arXiv - CS - Computers and Society Pub Date : 2020-09-17 , DOI: arxiv-2009.08281 Michael Lyons and Kazunori Morikawa
arXiv - CS - Computers and Society Pub Date : 2020-09-17 , DOI: arxiv-2009.08281 Michael Lyons and Kazunori Morikawa
A model of face representation, inspired by the biology of the visual system,
is compared to experimental data on the perception of facial similarity. The
face representation model uses aggregate primary visual cortex (V1) cell
responses topographically linked to a grid covering the face, allowing
comparison of shape and texture at corresponding points in two facial images.
When a set of relatively similar faces was used as stimuli, this Linked
Aggregate Code (LAC) predicted human performance in similarity judgment
experiments. When faces of perceivable categories were used, dimensions such as
apparent sex and race emerged from the LAC model without training. The
dimensional structure of the LAC similarity measure for the mixed category task
displayed some psychologically plausible features but also highlighted
differences between the model and the human similarity judgements. The human
judgements exhibited a racial perceptual bias that was not shared by the LAC
model. The results suggest that the LAC based similarity measure may offer a
fertile starting point for further modelling studies of face representation in
higher visual areas, including studies of the development of biases in face
perception.
中文翻译:
处理人脸的链接聚合代码(修订版)
受视觉系统生物学启发的面部表征模型与面部相似性感知的实验数据进行了比较。面部表征模型使用聚合初级视觉皮层 (V1) 细胞响应,在地形上与覆盖面部的网格相关联,允许比较两个面部图像中相应点的形状和纹理。当一组相对相似的人脸被用作刺激时,这个链接聚合代码(LAC)在相似性判断实验中预测了人类的表现。当使用可感知类别的面孔时,LAC 模型中出现了诸如明显性别和种族之类的维度,而无需进行训练。混合类别任务的 LAC 相似性度量的维度结构显示了一些心理上看似合理的特征,但也突出了模型与人类相似性判断之间的差异。人类的判断表现出种族感知偏见,这在 LAC 模型中是不存在的。结果表明,基于 LAC 的相似性度量可以为更高视觉区域中人脸表征的进一步建模研究提供一个肥沃的起点,包括研究人脸感知偏差的发展。
更新日期:2020-09-18
中文翻译:
处理人脸的链接聚合代码(修订版)
受视觉系统生物学启发的面部表征模型与面部相似性感知的实验数据进行了比较。面部表征模型使用聚合初级视觉皮层 (V1) 细胞响应,在地形上与覆盖面部的网格相关联,允许比较两个面部图像中相应点的形状和纹理。当一组相对相似的人脸被用作刺激时,这个链接聚合代码(LAC)在相似性判断实验中预测了人类的表现。当使用可感知类别的面孔时,LAC 模型中出现了诸如明显性别和种族之类的维度,而无需进行训练。混合类别任务的 LAC 相似性度量的维度结构显示了一些心理上看似合理的特征,但也突出了模型与人类相似性判断之间的差异。人类的判断表现出种族感知偏见,这在 LAC 模型中是不存在的。结果表明,基于 LAC 的相似性度量可以为更高视觉区域中人脸表征的进一步建模研究提供一个肥沃的起点,包括研究人脸感知偏差的发展。