Gibson Stuart J, Solomon Christopher J, Pallares-Bejarano Alvaro
School of Physical Sciences, University of Kent, Canterbury, England.
Behav Res Methods. 2005 Feb;37(1):170-81. doi: 10.3758/bf03206412.
A mathematical model previously developed for use in computer vision applications is presented as an empirical model for face space. The term appearance space is used to distinguish this from previous models. Appearance space is a linear vector space that is dimensionally optimal, enables us to model and describe any human facial appearance, and possesses characteristics that are plausible for the representation of psychological face space. Randomly sampling from a multivariate distribution for a location in appearance space produces entirely plausible faces, and manipulation of a small set of defining parameters enables the automatic generation of photo-realistic caricatures. The appearance space model leads us to the new concept of nonlinear caricatures, and we show that the accepted linear method for caricature is only a special case of a more general paradigm. Nonlinear methods are also viable, and we present examples of photographic quality caricatures, using a number of different transformation functions. Results of a simple experiment are presented that suggest that nonlinear transformations can accurately capture key aspects of the caricature effect. Finally, we discuss the relationship between appearance space, caricature, and facial distinctiveness. On the basis of our new theoretical framework, we suggest an experimental approach that can yield new evidence for the plausibility of face space and its ability to explain processes of recognition.
一个先前开发用于计算机视觉应用的数学模型被作为面部空间的经验模型呈现。使用“外观空间”这一术语来将其与先前的模型区分开来。外观空间是一个维度最优的线性向量空间，使我们能够对任何人类面部外观进行建模和描述，并且具有对于心理面部空间表示而言合理的特征。从外观空间中一个位置的多元分布进行随机采样会产生完全合理的面部，并且对一小组定义参数的操作能够自动生成逼真的漫画像。外观空间模型引领我们提出了非线性漫画像的新概念，并且我们表明公认的线性漫画像方法只是一个更通用范式的特殊情况。非线性方法也是可行的，并且我们展示了使用多种不同变换函数的高质量照片级漫画像示例。给出了一个简单实验的结果，表明非线性变换能够准确捕捉漫画像效果的关键方面。最后，我们讨论外观空间、漫画像和面部独特性之间的关系。基于我们新的理论框架，我们提出一种实验方法，该方法可以为面部空间的合理性及其解释识别过程的能力产生新的证据。
