A person’s visual aesthetics is an emerging behavioral biometric. Visual aesthetics can be defined as a person’s principles pertaining to their sense of beauty or fondness. Utilizing a person’s preference to certain images as discriminatory features forms the basis of person identification from visual aesthetics. This paper proposes a novel three-stage framework based on the convolutional neural network, AestheticNet, for the extraction of high-level features and identification of individuals from visual aesthetics. The rank-1 accuracy of 97.73% and rank-5 accuracy of 99.85% are achieved on the publicly available benchmark dataset, which outperforms all state-of-the-art methods.

中文翻译：

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AestheticNet：用于从视觉美学识别人物的深度卷积神经网络

一个人的视觉美学是一种新兴的行为生物特征。视觉美学可以定义为一个人关于他们的美感或喜好的原则。利用人对某些图像的偏好作为区分特征构成了从视觉美学上识别人的基础。本文提出了一种基于卷积神经网络 AestheticNet 的新型三阶段框架，用于从视觉美学中提取高级特征和识别个体。在公开可用的基准数据集上实现了 97.73% 的 1 级精度和 99.85% 的 5 级精度，其性能优于所有最先进的方法。