Benson P J, Campbell R, Harris T, Frank M G, Tovée M J
University Laboratory of Physiology, University of Oxford, England.
Percept Psychophys. 1999 Feb;61(2):259-74. doi: 10.3758/bf03206887.
Facial images can be enhanced by application of an algorithm--the caricature algorithm--that systematically manipulates their distinctiveness (Benson & Perrett, 1991c; Brennan, 1985). In this study, we first produced a composite facial image from natural images of the six facial expressions of fear, sadness, surprise, happiness, disgust, and anger shown on a number of different individual faces (Ekman & Friesen, 1975). We then caricatured the composite images with respect to a neutral (resting) expression. Experiment 1 showed that rated strength of the target expression was directly related to the degree of enhancement for all the expressions. Experiment 2, which used a free rating procedure, found that, although caricature enhanced the strength of the target expression (more extreme ratings), it did not necessarily enhance its purity, inasmuch as the attributes of nontarget expressions were also enhanced. Naming of prototypes, of original exemplar images, and of caricatures was explored in Experiment 3 and followed the pattern suggested by the free rating conditions of Experiment 2, with no overall naming advantage to caricatures under these conditions. Overall, the experiments suggested that computational methods of compositing and caricature can be usefully applied to facial images of expression. Their utility in enhancing the distinctiveness of the expression depends on the purity of expression in the source image.
通过应用一种算法——漫画算法，面部图像可以得到增强，该算法能系统地提升其独特性（本森和佩雷特，1991c；布伦南，1985）。在本研究中，我们首先从众多不同个体面部所展现的六种面部表情（恐惧、悲伤、惊讶、快乐、厌恶和愤怒）的自然图像中生成了一张合成面部图像（埃克曼和弗里森，1975）。然后，我们针对中性（静止）表情对合成图像进行了漫画化处理。实验1表明，对于所有表情，目标表情的评分强度与增强程度直接相关。实验2采用自由评分程序，发现虽然漫画化增强了目标表情的强度（评分更极端），但它不一定能提高其纯度，因为非目标表情的特征也得到了增强。实验3探究了原型、原始示例图像和漫画的命名情况，其结果遵循实验2自由评分条件所暗示的模式，即在这些条件下漫画并没有整体的命名优势。总体而言，这些实验表明，合成和漫画化的计算方法可以有效地应用于表情面部图像。它们在增强表情独特性方面的效用取决于源图像中表情的纯度。
