TY - GEN
T1 - The multimedia satellite task at MediaEval 2018
T2 - 2018 Working Notes Proceedings of the MediaEval Workshop, MediaEval 2018
AU - Bischke, Benjamin
AU - Helber, Patrick
AU - Zhao, Zhengyu
AU - De Bruijn, Jens
AU - Borth, Damian
PY - 2018
Y1 - 2018
N2 - This paper provides a description of the MediaEval 2018 Multimedia Satellite Task. The primary goal of the task is to extract and fuse content associated with events represent in Satellite Imagery and Social Media. Establishing a link from Satellite Imagery to Social Multimedia can yield to a comprehensive event representation which is vital for numerous applications. Focusing on natural disaster events, the main objective of the task is to leverage the combined event representation within the context of emergency response and environmental monitoring. In particular, our task focuses on flooding events and consists of two subtasks. The first Image Classification from Social Media subtask requires participants to retrieve images from Social Media that show a direct evidence for road passability during flooding events. The second task Flood Detection from Satellite Images aims to extract potentially flooded road sections from satellite images. The task seeks to go beyond state-of-the-art flooding map generation by focusing on information about road passability and the accessibility of urban infrastructure. Such information shows a clear potential to complement information from social images with satellite imagery for emergency management. Copyright held by the owner/author(s).
AB - This paper provides a description of the MediaEval 2018 Multimedia Satellite Task. The primary goal of the task is to extract and fuse content associated with events represent in Satellite Imagery and Social Media. Establishing a link from Satellite Imagery to Social Multimedia can yield to a comprehensive event representation which is vital for numerous applications. Focusing on natural disaster events, the main objective of the task is to leverage the combined event representation within the context of emergency response and environmental monitoring. In particular, our task focuses on flooding events and consists of two subtasks. The first Image Classification from Social Media subtask requires participants to retrieve images from Social Media that show a direct evidence for road passability during flooding events. The second task Flood Detection from Satellite Images aims to extract potentially flooded road sections from satellite images. The task seeks to go beyond state-of-the-art flooding map generation by focusing on information about road passability and the accessibility of urban infrastructure. Such information shows a clear potential to complement information from social images with satellite imagery for emergency management. Copyright held by the owner/author(s).
UR - http://www.scopus.com/inward/record.url?scp=85059835057&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85059835057&partnerID=8YFLogxK
UR - http://ceur-ws.org/Vol-2283
M3 - Conference contribution
AN - SCOPUS:85059835057
T3 - CEUR Workshop Proceedings
SP - 1
EP - 3
BT - MediaEval 2018 - Multimedia Benchmark Workshop
A2 - Larson, Martha
A2 - Arora, Piyush
A2 - Demarty, Claire-Hélène
A2 - Riegler, Michael
A2 - Bischke, Benjamin
A2 - Dellandrea, Emmanuel
A2 - Lux, Mathias
A2 - Porter, Alastair
A2 - Jones, Gareth J.F.
PB - CEUR-WS.org
Y2 - 29 October 2018 through 31 October 2018
ER -