Semi-Automatic Image Annotation.
Wenyin Liu, Susan Dumais, Yanfeng Sun, Hao Zhang, Mary Czerwinski, Brent A. Field
Abstract
Wenyin Liu, Susan Dumais, Yanfeng Sun, Hao Zhang, Mary Czerwinski, Brent A. Field
Abstract
: A novel approach to semi-automatically and progressively annotating images with keywords is presented. The progressive annotation process is embedded in the course of integrated keyword-based and content-based image retrieval and user feedback. When the user submits a keyword query and then provides relevance feedback, the search keywords are automatically added to the images that receive positive feedback and can then facilitate keyword-based image retrieval in the future. The coverage and quality of image annotation in such a database system is improved progressively as the cycle of search and feedback increases. The strategy of semi-automatic image annotation is better than manual annotation in terms of efficiency and better than automatic annotation in terms of accuracy. A performance study is presented which shows that high annotation coverage can be achieved with this approach, and a preliminary user study is described showing that users view annotations as important and will l...
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: A novel approach to semi-automatically and progressively annotating images with keywords is presented. The progressive annotation process is embedded in the course of integrated keyword-based and content-based image retrieval and user feedback. When the user submits a keyword query and then provides relevance feedback, the search keywords are automatically added to the images that receive positive feedback and can then facilitate keyword-based image retrieval in the future. The coverage and quality of image annotation in such a database system is improved progressively as the cycle of search and feedback increases. The strategy of semi-automatic image annotation is better than manual annotation in terms of efficiency and better than automatic annotation in terms of accuracy. A performance study is presented which shows that high annotation coverage can be achieved with this approach, and a preliminary user study is described showing that users view annotations as important and will l...
Key concepts: Relevance feedback, Computer science, Annotation, Image retrieval, Automatic image annotation, Information retrieval, Relevance (law), Process (computing)