Knowledge-Based Document Image Understanding

理解打印文档是一项智能活动。这项研究是关于自动化分析文档图像的一个方面，并获得其视觉内容的高级表示。文件包含照片和随附的文字。这一努力涉及到对由照片及其说明文字组成的交流单元的综合解释。当文字描述照片的突出方面时，有可能使用文字来指导视觉系统理解照片。这项研究有两个组成部分：第一部分涉及语言问题，第二部分涉及视觉子系统的开发。从文本中提取视觉信息的方法，特别是识别显著物体所需的线索，将被研究；这些信息可以基于语法和语义以各种形式呈现。文本提取的视觉线索在视觉对象识别中的作用也有待研究。为了验证这一理论，本文提出开发一个系统，利用分析报纸照片标题的结果来识别照片中的人脸。人脸定位子系统将结合尺度不变技术，以及基于存在的显著视觉特征来表征人脸的过滤器。//

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. //