Title

Ontology-aided feature correlation for multi-modal urban sensing

Publication Type

Conference Proceeding Article

Publication Date

5-2014

Abstract

The paper explores the use of correlation across features extracted from different sensing channels to help in urban situational understanding. We use real-world datasets to show how such correlation can improve the accuracy of detection of city-wide events by combining metadata analysis with image analysis of Instagram content. We demonstrate this through a case study on the Singapore Haze. We show that simple ontological relationships and reasoning can significantly help in automating such correlation-based understanding of transient urban events.

Keywords

Event Detection, Information Fusion, Multi-Modal Sensing

Discipline

OS and Networks

Research Areas

Data Management and Analytics

Publication

Ground/Air Multisensor Interoperability, Integration, and Networking for Persistent ISR VII, Baltimore, United States; 2016 April 18-20

Volume

9831

ISBN

9781510600720

Identifier

10.1117/12.2225143

Publisher

SPIE

City or Country

Baltimore

Additional URL

http://doi.org./10.1117/12.2225143

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