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Method of recognizing partially occluded and/or imprecisely localized faces

机译:识别部分遮挡和/或不精确定位的面部的方法

摘要

A method of recognizing a test face given an imprecise localization and/or a partially occluded face. Using an eigenspace representation of the test face, a subspace is computed that represents localization errors within the eigenspace. This is computed by calculating an actual localization error of the localization of the test face. Accounting for the calculated actual localization error, all possible morphed faces are projected onto the eigenspace. For all possible faces, the subspace is modeled where all of the possible localizations of the possible faces lie using of a Gaussian distribution. To accommodate for possible partial occlusions, for all possible faces, the possible faces are divided into n different local parts. Each of the n local parts are modeled using a Gaussian distribution. A global identity of the test face is computed by adding all local probabilities defined by the Gaussian distribution. The test face is recognized based on the computed subspace and/or the accounted for possible partial occlusions.
机译:一种识别给定的定位不精确和/或部分遮挡的测试面的方法。使用测试面的特征空间表示,可以计算一个子空间,该子空间表示特征空间内的定位误差。这是通过计算测试面定位的实际定位误差来计算的。考虑到计算出的实际定位误差,所有可能的变形面都投影到本征空间上。对于所有可能的人脸,在使用可能的人脸的所有可能的本地化都使用高斯分布的情况下对子空间进行建模。为了适应可能的部分遮挡,对于所有可能的面部,将可能的面部分为n个不同的局部。 n个局部部分中的每一个都使用高斯分布建模。通过添加高斯分布定义的所有局部概率来计算测试面的全局标识。基于计算出的子空间和/或考虑到可能的部分遮挡来识别测试面。

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