Abstract
The emergence of social media has provided vast amounts of information that is potentially valuable for emergency management. In the EU-FP7 Project Security Systems for Language and Image Analysis (Slandail), an image analysis system has been developed to recognize the flood water images from the social media resources by incorporating with text analysis. A novel image feature descriptor has been developed to facilitate fast image processing based on incorporation of the "Squiral" (Square-Spiral) Image Processing (SIP) framework with the "Speeded-up Robust Features" (SURF). A new approach is proposed to generate an index from image recognition outcomes based on a moving window average, which presents a temporal change based on the occurrence of flooding water identified by image analysis. The evaluation for computation time and recognition were based on a batch of images obtained from the US Federal Emergency Management Agency (FEMA) media library and Facebook corpus from Germany, and the outcomes show the advantages of the proposed image features. The simulation results demonstrate the concept of the index based on a moving window average, highlighting the potential for application in emergency management.
Original language | English |
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Title of host publication | Unknown Host Publication |
Publisher | IEEE |
Pages | 805-810 |
Number of pages | 6 |
ISBN (Print) | 978-1-5090-0990-9 |
DOIs | |
Publication status | Published online - 15 Dec 2016 |
Event | 11th International Conference on Availability, Reliability and Security (ARES), 2016 - Austria Duration: 15 Dec 2016 → … |
Workshop
Workshop | 11th International Conference on Availability, Reliability and Security (ARES), 2016 |
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Period | 15/12/16 → … |
Keywords
- emergency management
- flood event image recognition
- fast image processing
- social media analysis