A probabilistic topic-connection model for automatic image annotation

The explosive increase of image data on Internet has made it an important, yet very challenging task to index and automatically annotate image data. To achieve that end, sophisticated algorithms and models have been proposed to study the correlation between image content and corresponding text description. Despite the success of previous works, however, researchers are still facing two major difficulties that may undermine their effort of providing reliable and accurate annotations for images. The first difficulty is lacking of comprehensive benchmark image dataset with high quality text descriptions. The second difficulty is lacking of effective way to represent the image content and make it associate with the text descriptions. In our paper, we aim to deal with both problems. To deal with the first problem, we utilize Wikipedia as external knowledge source and enrich the ontology structure of ImageNet database with comprehensive and highly-reliable text descriptions from Wikipedia a...

• Type: Journal
• Year: 2010
• Where: CIKM
• Authors: Xin Chen, Xiaohua Hu, Zhongna Zhou, Caimei Lu, Gail Rosen, Tingting He, E. K. Park
• Keywords: Automatic Image Annotation, CIKM 2010, Image, Information Technology, Text Description