Ulster University Logo

Flood Event Image Recognition via Social Media Image and Text Analysis

Jing, Min, Scotney, Bryan, Coleman, SA, McGinnity, T.Martin, Kelly, Stephen, Zhang, Xiubo, Ahmad, Khurshid, Schlaf, Antje, Grunder-Fahrer, Sabine and Heyer, Gerhard (2016) Flood Event Image Recognition via Social Media Image and Text Analysis. In: COGNITIVE 2016 : The Eighth International Conference on Advanced Cognitive Technologies and Applications, Rome, Italy. IARIA. 6 pp. [Conference contribution]

[img] Text - Supplemental Material
Indefinitely restricted to Repository staff only.

18kB
[img] Text - Accepted Version
617kB

Abstract

The emergence of social media has led to a new era of information communication, in which vast amounts of information are available that is potentially valuable for emergency management. This supplements and enhances the data available through government bodies, emergency response agencies, and broadcasters. Techniques developed for visual content analysis can be useful tools to improve current emergency management systems. We present a new flood event scene recognition system based on social media visual content and text analysis. The concept of ontology is introduced that enables the text and image analysis to be linked at an atomic or hierarchical level. We accelerate web image analysis by using a new framework that incorporates a novel “Squiral” (square spiral) Image Processing addressing scheme with the state-of-art “Speeded-up Robust Features”. The focus of recognition was to identify the water or person images from the background images. Image URLs were obtained based on text analysis using English and German languages. We demonstrate the efficiency of the new image features and accuracy of recognition of flood water and persons within images, and hence the potential to enhance emergency management systems. The system for the atomic level recognition was evaluated using flood event related image data available from the US Federal Emergency Management Agency media library and public German Facebook pages and groups related to flood and flood aid. This evaluation was performed for and on behalf of an EU-FP7 Project Security Systems for Language and Image Analysis (Slandail), a system for managing disasters specifically with the help of digital media including social and legacy media. The system is intended to be incorporated by the project technology partners CID GmBH and DataPiano SA.

Item Type:Conference contribution (Paper)
Keywords:flood event recognition; fast image processing; social media analysis; multimodal data fusion; emergency management
Faculties and Schools:Faculty of Computing & Engineering
Faculty of Computing & Engineering > School of Computing and Information Engineering
Faculty of Computing & Engineering > School of Computing and Intelligent Systems
Research Institutes and Groups:Computer Science Research Institute > Intelligent Systems Research Centre
Computer Science Research Institute
Computer Science Research Institute > Information and Communication Engineering
ID Code:36096
Deposited By: Dr Sonya Coleman
Deposited On:21 Feb 2017 14:01
Last Modified:21 Feb 2017 14:01

Repository Staff Only: item control page