The importance of spatial frequency and familiarity in face recognition
The importance of spatial frequency and familiarity in face recognition
复制标题
空间频率和熟悉度在人脸识别中的重要性
DOI：
10.1167/7.9.4
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发表时间：
2007
影响因子：
1.8
通讯作者：
Q. Vuong
中科院分区：
文献类型：
--
作者：
K. Pilz;H. Bülthoff;Q. Vuong
使用延迟视觉搜索范例，我们表明，非刚性移动的脸比静态脸更好地编码（Pilz. Thornton and Bülthoff，2006）.在这个任务中，观察者学习一个动态和一个静态的脸，然后在一个静态搜索数组中搜索任何一个目标。在这里，我们使用高（HSF）和低（LSF）频率过滤的脸在视觉搜索，调查是否存在差异在于不同的空间频率的编码。在实验1（N= 12）中，我们使用了一个学习程序，只需要观察员评价目标沿着不同的性格特征。我们发现动态学习的面孔没有优势，但HSF面孔识别得更准确（p [lt]]。05）。在实验2中，我们使用了我们之前的学习程序，要求观察者使用详细的问卷来评估目标的个性和面部特征。观察者（N= 8）在寻找动态学习的面孔方面更快（p [lt]]。05），更准确地找到LSF的脸（p= 0.07）。综上所述，这些结果表明，学习的性质可以影响面孔编码策略。此外，频率效应表明，不太熟悉的面孔可能更多地从特征中识别，而不是从特征信息中识别。在实验3中，我们测试了动态优势是否是由于更高的熟悉度的动态学习的面孔。观察员（N= 8）寻找一个同事和一个不熟悉的面孔，从实验2的程序学习。我们发现观察者更快（p [lt]]）。01)更准确地说，01)这表明动态优势部分取决于对目标面孔的熟悉程度。
Using a delayed visual search paradigm, we showed that non-rigidly moving faces are better encoded than static faces (Pilz. Thornton and Bülthoff, 2006). In this task, observers learned one dynamic and one static face, and then searched for either target in a static search array. Here, we used high (HSF) and low (LSF) frequency filtered faces during visual search to investigate whether the difference lies in the encoding of different spatial frequencies. In Experiment 1 (N= 12), we used a learning procedure which only required observers to rate the targets along different character traits. We found no advantage for dynamically-learned faces, but HSF faces were recognized more accurately (p [[lt]]. 05). In Experiment 2, we used our previous learning procedure which required observers to assess both targets' personality and facial features using a detailed questionnaire. Observers (N= 8) were faster at finding dynamically-learned faces (p [[lt]]. 05), and more accurate at finding LSF faces (p= 0.07). Taken together, these results show that the nature of learning can affect face encoding strategies. Furthermore, the frequency effects suggest that less familiar faces may be recognized more from features than from configural information. In Experiment 3, we tested whether the dynamic advantage was due to the higher familiarity of dynamically-learned faces. Observers (N= 8) searched for a colleague and an unfamiliar face, learned with the procedure from Experiment 2. We found that observers were faster (p [[lt]]. 01) and more accurate (p [[lt]]. 01) at finding their colleagues, which suggests that the dynamic advantage partly depends on the level of familiarity with the target face.