Is it an animal?: Is it a human face?: Fast processing in upright and inverted natural scenes
Is it an animal?: Is it a human face?: Fast processing in upright and inverted natural scenes
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DOI：
10.1167/3.6.5
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发表时间：
2003-01-01
影响因子：
1.8
通讯作者：
Fabre-Thorpe, M
中科院分区：
文献类型：
--
作者：
Rousselet, GA;Macé, MJM;Fabre-Thorpe, M
对象分类可以非常快。但在所有物体中，人脸可能拥有一种特殊的地位，这种地位可能取决于一个专门的模块。因此，对人脸的视觉处理可能比对任何其他类型的物体都要快。此外，由于面部处理可能依赖于面部结构，它可能会被刺激反转破坏。在这里，我们报告了两个实验，比较了快速分类的人脸和动物或动物的面孔的上下文中直立和倒置的自然场景。在实验1中，自然场景包含人脸和动物在一个完整的范围内，从近距离到远的看法。在实验2中，目标被限制在人脸和动物脸的特写镜头。这两个实验都揭示了我们的视觉系统对物体的处理效率，并进一步表明：（1）面孔与动物相比几乎没有优势;（2）反转对表现的损害很小;（3）面孔对反转的敏感性更高。这些结果被解释在一个独特的系统，在腹侧通路的对象处理的框架内。在这个系统中，证据将非常快速和有效地积累，以分类视觉对象，而不涉及面部模块或心理旋转机制。它进一步表明，在自然场景中的快速对象分类可能不依赖于高层次的功能，而是中间复杂的功能。
Object categorization can be extremely fast. But among all objects, human faces might hold a special status that could depend on a specialized module. Visual processing could thus be faster for faces than for any other kind of object. Moreover, because face processing might rely on facial configuration, it could be more disrupted by stimulus inversion. Here we report two experiments that compared the rapid categorization of human faces and animals or animal faces in the context of upright and inverted natural scenes. In Experiment 1, the natural scenes contained human faces and animals in a full range of scales from close-up to far views. In Experiment 2, targets were restricted to close-ups of human faces and animal faces. Both experiments revealed the remarkable object processing efficiency of our visual system and further showed (1) virtually no advantage for faces over animals; (2) very little performance impairment with inversion; and (3) greater sensitivity of faces to inversion. These results are interpreted within the framework of a unique system for object processing in the ventral pathway. In this system, evidence would accumulate very quickly and efficiently to categorize visual objects, without involving a face module or a mental rotation mechanism. It is further suggested that rapid object categorization in natural scenes might not rely on high-level features but rather on features of intermediate complexity.