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A Probabilistic Approach to Semantic Face Retrieval System

机译:语义人脸检索系统的概率方法

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摘要

A probabilistic system that retrieves face images based on verbal descriptions given by users is proposed. This interactive system prompts the user at each stage of query to provide a description about a facial feature that will help it to retrieve the required face image. It is a soft biometric system that groups people by the description of their faces. The method proposed automates the process of extracting general verbal descriptions of faces like 'long nosed' or 'blonde haired' and performs queries on them. The proposed method uses Bayesian learning for the query process and hence is more immune to errors in both the extraction of semantic descriptions and user given information. It was found that the required face image appeared 77.6% of the time within the top 5 and 90.4% of the time within the top 10 retrieved face images.
机译:提出了一种基于用户给出的口头描述来检索面部图像的概率系统。该交互式系统提示用户在查询的每个阶段提供有关面部特征的描述,以帮助其检索所需的面部图像。这是一种软生物识别系统,可通过对人脸的描述对其进行分组。提出的方法使提取“长鼻子”或“金发”等面孔的一般语言描述的过程自动化,并对它们进行查询。所提出的方法将贝叶斯学习用于查询过程,因此在语义描述的提取和用户给定信息方面都更不受错误的影响。发现所需的面部图像在前5个检索到的面部图像中出现的时间为77.6%,在前10个面部图像中出现的时间为90.4%。

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