@inproceedings{d0bbc16953ad49c48e0c814a25e2eacd,
title = "Ontology-aided feature correlation for multi-modal urban sensing",
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",
author = "Archan Misra and Zaman Lantra and Kasthuri Jayarajah",
note = "Publisher Copyright: {\textcopyright} 2016 SPIE.; Ground/Air Multisensor Interoperability, Integration, and Networking for Persistent ISR VII ; Conference date: 18-04-2016 Through 20-04-2016",
year = "2016",
doi = "10.1117/12.2225143",
language = "English (US)",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "Kolodny, {Michael A.} and Tien Pham",
booktitle = "Ground/Air Multisensor Interoperability, Integration, and Networking for Persistent ISR VII",
address = "United States",
}