A proposal for a Riemannian face space and application to atypical vs. typical face similarities

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS
James T. Townsend , Hao-Lun Fu , Cheng-Ju Hsieh , Cheng-Ta Yang
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引用次数: 0

Abstract

Two intriguing papers of the late 1990’s and early 2000s by J. Tanaka and colleagues put forth the hypothesis that a repository of face memories can be viewed as a vector space where points in the space represent faces and each of these is surrounded by an attractor field. This hypothesis broadens the thesis of T. Valentine that face space is constituted of feature vectors in a finite dimensional vector space (e.g., Valentine, 2001). The attractor fields in the atypical part of face space are broader and stronger than those in typical face regions. This notion makes the substantiated prediction that a morphed midway face between a typical and atypical parent will be perceptually more similar to the atypical face. We propose an alternative interpretation that takes a more standard geometrical approach but also departs from the popular types of metrics assumed in almost all multidimensional scaling studies. Rather we propose a theoretical structure based on our earlier investigations of non-Euclidean and especially, Riemannian Face Manifolds (e.g., Townsend, Solomon, & Spencer-Smith, 2001). We assert that this approach avoids some of the issues involved in the gradient theme by working directly with the type of metric inherently associated with the face space. Our approach emphasizes a shift towards a greater emphasis on non-Euclidean geometries, especially Riemannian manifolds, integrating these geometric concepts with processing-oriented modeling. We note that while fields like probability theory, stochastic process theory, and mathematical statistics are commonly studied in mathematical psychology, there is less focus on areas like topology, non-Euclidean geometry, and functional analysis. Therefore, both to elevate comprehension as well as to propagate the latter topics as critical for our present and future enterprises, our exposition moves forward in a highly tutorial fashion, and we embed the material in its proper historical context.

关于黎曼面孔空间的建议以及非典型面孔与典型面孔相似性的应用
J. Tanaka 及其同事在 20 世纪 90 年代末和 21 世纪初发表了两篇引人入胜的论文,提出了一个假设:人脸记忆库可被视为一个向量空间,空间中的点代表人脸,而每个点都被一个吸引域所包围。这一假设拓宽了瓦伦丁(T. Valentine)的理论,即人脸空间是由有限维向量空间中的特征向量构成的(例如,瓦伦丁,2001 年)。人脸空间非典型部分的吸引场比典型人脸区域的吸引场更宽更强。这一概念证实了这样的预测,即介于典型和非典型母体之间的变形中间脸在知觉上会与非典型脸更加相似。我们提出了另一种解释,它采用了一种更标准的几何方法,但也偏离了几乎所有多维缩放研究中假设的流行度量类型。相反,我们提出的理论结构是基于我们早期对非欧几里得,特别是黎曼面图的研究(例如,Townsend, Solomon, & Spencer-Smith, 2001)。我们认为,这种方法通过直接使用与人脸空间固有相关的度量类型,避免了梯度主题所涉及的一些问题。我们的方法强调转向更加重视非欧几里得几何,特别是黎曼流形,将这些几何概念与面向处理的建模相结合。我们注意到,虽然数学心理学通常研究概率论、随机过程理论和数理统计等领域,但较少关注拓扑学、非欧几里得几何和函数分析等领域。因此,为了提高理解能力,并宣传后者对我们现在和未来的事业至关重要,我们的论述以高度辅导的方式进行,并将材料嵌入其适当的历史背景中。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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