分离水平和空间位置对三维物体识别的影响

物体识别的两大理论一直存在争议。以物体为中心理论认为不管物体出现在什么位置,识别均与空间位置无关,而以观察者为中心理论认为识别与空间位置有关。研究参照物体识别的“小几何体”思想自制实验材料,采用启动范式下的分类任务,通过操纵物体自身的结构信息和相对的结构信息,考察了三维物体识别的影响机制。结果发现：（1）物体自身组成部分之间的分离水平和物体之间的相对空间位置对物体识别的影响均呈层级式。支持以观察者为中心理论的整体表征观;（2）不分离水平和相同位置上,整体启动快于部分启动;全分离水平和远距离位置上,部分启动快于整体启动。支持以物体为中心理论的小几何体优先加工观。实现两大理论的融合需要进一步厘清“What + Where”两通路联合表征的二级子层级。     

Face Recognition Depends on Specialized Mechanisms Tuned to View-Invariant Facial Features: Insights from Deep Neural Networks Optimized for Face or Object Recognition

Face recognition is a computationally challenging classification task. Deep convolutional neural networks (DCNNs) are brain-inspired algorithms that have recently reached human-level performance in face and object recognition. However, it is not clear to what extent DCNNs generate a human-like representation of face identity. We have recently revealed a subset of facial features that are used by humans for face recognition. This enables us now to ask whether DCNNs rely on the same facial information and whether this human-like representation depends on a system that is optimized for face identification. In the current study, we examined the representation of DCNNs of faces that differ in features that are critical or non-critical for human face recognition. Our findings show that DCNNs optimized for face identification are tuned to the same facial features used by humans for face recognition. Sensitivity to these features was highly correlated with performance of the DCNN on a benchmark face recognition task. Moreover, sensitivity to these features and a view-invariant face representation emerged at higher layers of a DCNN optimized for face recognition but not for object recognition. This finding parallels the division to a face and an object system in high-level visual cortex. Taken together, these findings validate human perceptual models of face recognition, enable us to use DCNNs to test predictions about human face and object recognition as well as contribute to the interpretability of DCNNs.     

三维物体识别的心理表征：角度依赖还是角度独立

“物体识别是角度独立还是角度依赖”的问题一直存在着争议。以物体为中心理论认为是角度独立, 以观察者为中心理论认为是角度依赖。研究参照物体识别的“小几何体”思想自制实验材料, 采用启动范式, 在两个实验中通过考察结构信息和视图信息对物体识别的影响, 揭示物体识别的心理表征。结果发现: (1)形状信息和类别空间关系信息影响物体识别, 表明以物体为中心理论对物体识别表征机制解释的合理性; (2)角度信息可能独立于形状信息表征, 深度旋转方式下的识别成绩优于平面旋转, 表明以观察者为中心理论能够更好地解释三维物体识别的深度旋转现象。研究结果为物体识别理论的融合提供了实证依据。