Retrieving Social Flooding Images Based on Multimodal Information

This paper presents the participation of the RU-DS team at the MediaEval 2017 Multimedia Satellite Task. We design a system for retrieving social images that show direct evidence of flooding events using a multimodal approach based on visual features from images and the corresponding metadata. Specifically, we implement preprocessing operations including image cropping and test-set pre-filtering based on image color complexity or textual metadata, as well as re-ranking for fusion. Tests on the YFCC100M-Dataset show that the fusion-based approach outperforms the methods based on only visual features or metadata.