Paper: Generating Image Descriptions Using Dependency Relational Patterns

ACL ID P10-1127
Title Generating Image Descriptions Using Dependency Relational Patterns
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2010
Authors

This paper presents a novel approach to automatic captioning of geo-tagged images by summarizing multiple web- documents that contain information re- lated to an image’s location. The summa- rizer is biased by dependency pattern mod- els towards sentences which contain fea- tures typically provided for different scene types such as those of churches, bridges, etc. Our results show that summaries bi- ased by dependency pattern models lead to significantly higher ROUGE scores than both n-gram language models reported in previous work and also Wikipedia base- line summaries. Summaries generated us- ing dependency patterns also lead to more readable summaries than those generated without dependency patterns.