Knowledge-Based Document Image Understanding

理解印刷文档是一项智力活动。 这项研究是关于自动化分析文档图像并导出其视觉内容的高级表示的一个方面。 文档包含照片和随附文本。 这项工作涉及对由照片及其标题组成的交流单元进行综合解释。 当文本描述照片的显着方面时，可以使用文本来指导视觉系统理解照片。 这项研究有两个组成部分：第一个部分涉及语言问题，第二个部分涉及视觉子系统的开发。 有待研究从文本中提取视觉信息的方法，特别是识别显着对象所需的线索； 此类信息可以基于语法和语义以多种形式呈现。 文本提取的视觉线索在执行视觉对象识别中的作用也有待研究。 作为对该理论的测试，建议开发一个系统，其中解析报纸照片标题的结果用于识别照片中的人脸。 面部定位子系统将结合尺度不变技术和基于区分视觉特征的存在来表征面部的过滤器。 //

Understanding printed documents is an intelligent activity. This research is about automating one aspect of analyzing a document image and deriving a high-level representation of its visual content. Documents contain photographs and accompanying text. This effort is concerned with arriving at an integrated interpretation of the communicative unit consisting of photographs and their captions. When text describes salient aspects of a photograph, it is possible to use the text to direct a vision system in understanding the photograph. There are two components to this research: the first deals with language issues and the second with development of a vision subsystem. Methods of extracting visual information from text, specifically cues required to identify salient objects, are to be studied; such information may be present in a variety of forms, based on both syntax and semantics. The role of textually extracted visual cues in performing visual object recognition is also to be studied. As a test of the theory, it is proposed to develop a system where the result of parsing a caption of a newspaper photograph is used to identify human faces in the photograph. The face location subsystem will incorporate scale invariant techniques, and filters that characterize faces based on the presence of distinguishing visual features. //