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首页> 外文会议>Human Vision and Electronic Imaging XI; Electronic Imaging Science and Technology >Using Words as Lexical Basis Functions for Automatically Indexing Face Images in a Manner That Correlates With Human Perception of Similarity
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Using Words as Lexical Basis Functions for Automatically Indexing Face Images in a Manner That Correlates With Human Perception of Similarity

机译：使用单词作为词法基础功能，以自动索引人脸图像的方式与人类对相似性的感知相关

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摘要

To facilitate collaboration between computers and people, computers should be able to perceive the world in a manner that correlates well with human perception. A good example of this is face image retrieval. Mathematically-based face indexing methods that are not based primarily on how humans perceive faces can produce retrievals that are disappointing to human users. This raises the question "Can human faces be automatically indexed in a manner that correlates well with human perception of similarity?" Humans use words to describe faces - words such as braided, graybearded, bearded, bespectacled, bald, blondish, blond, freckled, blue eyed, mustached, pale, Caucasian, brown eyed, dark skinned, or black eyed. Such words represent dimensions that span a shared concept space for faces. Therefore they might provide a useful guide to indexing faces in an intuitive manner. This paper describes research that uses descriptive words such as these to index faces. Each word guides the design of one feature detector that produces a scalar coefficient, and those coefficients collectively define a feature vector for each face. Given these feature vectors, it is possible to compute a similarity measure between pairs of faces, and to compare that computed similarity to the similarity, as perceived by humans.
机译：为了促进计算机与人之间的协作，计算机应该能够以与人类感知紧密相关的方式感知世界。面部图像检索就是一个很好的例子。基于数学的面部索引方法并非主要基于人类如何感知面部会产生令人失望的检索结果。这就提出了一个问题：“可以以与人类对相似性的感知很好地相关的方式来自动索引人脸吗？”人类使用单词来描述面孔-诸如辫子，灰胡子，胡须，带眼镜，秃头，金发，金发，雀斑，蓝眼睛，胡子，苍白，白种人，棕眼，黑皮肤或黑眼之类的词。这样的词表示跨越面部共享概念空间的尺寸。因此，它们可以为以直观方式索引人脸提供有用的指导。本文介绍了使用诸如此类的描述性词来索引人脸的研究。每个词指导一个特征检测器的设计，该特征检测器产生一个标量系数，这些系数共同定义每个面部的特征向量。给定这些特征向量，就有可能计算出两对脸部之间的相似度，并将计算出的相似度与人类所感觉到的相似度进行比较。

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