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Proceedings Paper

Ontology-aided feature correlation for multi-modal urban sensing
Author(s): Archan Misra; Zaman Lantra; Kasthuri Jayarajah
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Paper 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.

Paper Details

Date Published: 12 May 2016
PDF: 10 pages
Proc. SPIE 9831, Ground/Air Multisensor Interoperability, Integration, and Networking for Persistent ISR VII, 98310A (12 May 2016); doi: 10.1117/12.2225143
Show Author Affiliations
Archan Misra, Singapore Management Univ. (Singapore)
Zaman Lantra, Univ. of Moratuwa (Sri Lanka)
Kasthuri Jayarajah, Singapore Management Univ. (Singapore)


Published in SPIE Proceedings Vol. 9831:
Ground/Air Multisensor Interoperability, Integration, and Networking for Persistent ISR VII
Michael A. Kolodny; Tien Pham, Editor(s)

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