论文标题
用于处理面的链接聚合代码(修订版)
A Linked Aggregate Code for Processing Faces (Revised Version)
论文作者
论文摘要
将面部表示模型与视觉系统生物学的启发,与面部相似性感知的实验数据进行了比较。面部表示模型使用骨料主视觉皮层(V1)细胞响应在地形上链接到覆盖面的网格,从而可以比较两个面部图像中相应点的形状和纹理。当将一组相对相似的面孔用作刺激时,该连接的骨料代码(LAC)预测了相似性判断实验中的人类绩效。当使用可感知类别的面孔时,在没有训练的情况下,从LAC模型出现了明显的性别和种族等维度。混合类别任务的LAC相似性度量的维度结构显示了一些在心理上合理的特征,但也强调了模型和人类相似性判断之间的差异。人类的判断表现出一种种族感知偏见,而LAC模型并未共享。结果表明,基于LAC的相似性度量可能为在较高视觉区域的面部表征进行进一步建模研究(包括研究面部感知的发展)提供了一个肥沃的起点。
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.