Web上基于内容的图像检索的自动反馈

Y. Aslandogan, Clement T. Yu
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引用次数: 8

摘要

我们解决了在没有现有面部图像数据库的情况下,在大型集合(如Web)中识别人物图像的问题。本文描述了一种方法和系统,利用从网络上获取的文本证据自动构建一个初始人脸图像数据库,然后使用该数据库对该人的图像进行识别。通过文本/HTML分析和人脸检测获得初始检索结果。内部聚类过程将这些初始结果中视觉上相似的人脸分组,并构建人脸数据库。这个数据库然后被面部识别器使用。文本和视觉证据模块的输出使用Dempster-Shafer(1976)证据组合公式进行组合。我们提出了一个实验评估的结果,当文本/HTML分析表现不佳时,系统能够改进仅检测方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Automatic feedback for content based image retrieval on the Web
We address the problem of identifying images of persons in large collections, such as the Web, without an existing face image database. We describe a method and a system that automatically constructs an initial face image database for a person using textual evidence obtained from the Web, and then uses this database for identifying images of that person. The initial retrieval results are obtained via text/HTML analysis and face detection. An internal clustering process groups visually similar faces among these initial results and builds a facial database. This database is then used by a face recognizer. The outputs of the textual and visual evidence modules are combined using Dempster-Shafer (1976) evidence combination formula. We present the results of an experimental evaluation where the system was able to improve upon the detection-only method when text/HTML analysis performed poorly.
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