Flood Level Prediction via Human Pose Estimation from Social Media Images

Floods are the most common natural and among the most dangerous disasters in the world. It is important to get up-to-date information about flooding and the flood level for flood preparation and prevention. In this paper, we propose an efficient method to determine the flood level from daily activity photos on social media. Our method is based on the idea of matching the water level with human pose to determine the level of severity of flooding. Extensive experiments conducted on the dataset of Multimodal Flood Level Estimation show the superiority of our proposed method. We achieve the first rank in MediaEval 2019 and this demonstrates the potential applications of our method to analyze flood information.