Semantic knowledge extraction and annotation for web images

Nowadays, images have become widely available on the World Wide Web (WWW). It’s essential to develop effective ways for managing and retrieving such abundant images. Advantageously, compared to the traditional images where very little information is provided, the web images contain plentiful context data. This paper introduces a system that can automatically acquire semantic knowledge for web image annotation. By using a page layout analysis method that can precisely assign context to web images, we developed efficient algorithms to extract semantic knowledge for web images, such as description, people, temporal and geographic information. To validate the practicality and efficiency of this system, we applied it to about 6,500 images crawled from Web. Experiments demonstrated that our approach could achieve satisfactory results. Categories and Subject Descriptors H.3.m [Information Storage and Retrieval]: Miscellaneous General Terms: Experimentation

• Type: Conference
• Year: 2005
• Where: MM
• Authors: Zhigang Hua, Xiang-Jun Wang, Qingshan Liu, Hanqing Lu
• Keywords: MM 2005, Semantic Knowledge, Web Images, Web Images Contain