Improving Automatic Image Captioning Using Text Summarization Techniques

This paper presents two different approaches to automatic captioning of geo-tagged images by summarizing multiple web-documents that contain information related to an image’s location: a graph-based and a statistical-based approach. The graph-based method uses text cohesion techniques to identify information relevant to a location. The statistical-based technique relies on different word or noun phrases frequency counting for identifying pieces of information relevant to a location. Our results show that summaries generated using these two approaches lead indeed to higher ROUGE scores than n-gram language models reported in previous work.

• Type: Journal
• Year: 2010
• Where: TSD
• Authors: Laura Plaza, Elena Lloret, Ahmet Aker
• Keywords: N-gram Language Models, Noun Phrases Frequency, Signal Processing, Text Cohesion Techniques, TSD 2010