loading
Documents

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Marcos V. N. Bedo ; Gustavo Blanco ; Willian D. Oliveira ; Mirela T. Cazzolato ; Alceu F. Costa ; Jose F. Rodrigues Jr. ; Agma J. M. Traina and Caetano Traina Jr.

Affiliation: University of São Paulo, Brazil

ISBN: 978-989-758-096-3

Keyword(s): Fire Detection, Feature Extraction, Evaluation Functions, Image Descriptors, Social Media.

Related Ontology Subjects/Areas/Topics: Applications of Expert Systems ; Artificial Intelligence ; Artificial Intelligence and Decision Support Systems ; Data Mining ; Databases and Information Systems Integration ; Enterprise Information Systems ; Human-Computer Interaction ; Multimedia Systems ; Sensor Networks ; Signal Processing ; Soft Computing

Abstract: Crowdsourcing and social media could provide valuable information to support decision making in crisis management, such as in accidents, explosions and fires. However, much of the data from social media are images, which are uploaded in a rate that makes it impossible for human beings to analyze them. Despite the many works on image analysis, there are no fire detection studies on social media. To fill this gap, we propose the use and evaluation of a broad set of content-based image retrieval and classification techniques for fire detection. Our main contributions are: (i) the development of the Fast-Fire Detection method (FFireDt), which combines feature extractor and evaluation functions to support instance-based learning; (ii) the construction of an annotated set of images with ground-truth depicting fire occurrences – the Flickr-Fire dataset; and (iii) the evaluation of 36 efficient image descriptors for fire detection. Using real data from Flickr, our results showed that FFireDt was able to achieve a precision for fire detection that was comparable to that of human annotators. Therefore, our work shall provide a solid basis for further developments on monitoring images from social media and crowdsourcing. (More)

PDF ImageFull Text

Download
Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 54.198.205.153

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
V. N. Bedo M., Blanco G., D. Oliveira W., T. Cazzolato M., F. Costa A., F. Rodrigues Jr. J., J. M. Traina A. and Traina Jr. C. (2015). Techniques for Effective and Efficient Fire Detection from Social Media Images.In Proceedings of the 17th International Conference on Enterprise Information Systems - Volume 1: ICEIS, ISBN 978-989-758-096-3, pages 34-45. DOI: 10.5220/0005341500340045

@conference{iceis15,
author={Marcos V. N. Bedo and Gustavo Blanco and Willian D. Oliveira and Mirela T. Cazzolato and Alceu F. Costa and Jose F. Rodrigues Jr. and Agma J. M. Traina and Caetano Traina Jr.},
title={Techniques for Effective and Efficient Fire Detection from Social Media Images},
booktitle={Proceedings of the 17th International Conference on Enterprise Information Systems - Volume 1: ICEIS,},
year={2015},
pages={34-45},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005341500340045},
isbn={978-989-758-096-3},
}

TY - CONF

JO - Proceedings of the 17th International Conference on Enterprise Information Systems - Volume 1: ICEIS,
TI - Techniques for Effective and Efficient Fire Detection from Social Media Images
SN - 978-989-758-096-3
AU - V. N. Bedo M.
AU - Blanco G.
AU - D. Oliveira W.
AU - T. Cazzolato M.
AU - F. Costa A.
AU - F. Rodrigues Jr. J.
AU - J. M. Traina A.
AU - Traina Jr. C.
PY - 2015
SP - 34
EP - 45
DO - 10.5220/0005341500340045

Login or register to post comments.

Comments on this Paper: Be the first to review this paper.