Joint Proceedings of the 19th World Congress of the International Fuzzy Systems Association (IFSA), the 12th Conference of the European Society for Fuzzy Logic and Technology (EUSFLAT), and the 11th International Summer School on Aggregation Operators (AGOP)

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Audio Surveillance of Road Traffic: An Approach Based on Anomaly Detection and Interval Type-2 Fuzzy Sets

Authors
Stefano Rovetta, Zied Mnasri, Francesco Masulli, Alberto Cabri
Corresponding Author
Stefano Rovetta
Available Online 30 August 2021.
DOI
10.2991/asum.k.210827.059How to use a DOI?
Keywords
Audio event detection, audio surveillance, anomaly detection, deep autoencoder, fuzzy membership, interval comparison
Abstract

Surveillance systems are increasingly exploiting multimodal information for improved effectiveness. This paper presents an audio event detection method for road traffic surveillance, combining generative deep autoencoders and fuzzy modelling to perform anomaly detection. Baseline deep autoencoders are used to compute the reconstruction error of each audio segment, which provides a primary estimation of outlierness. To account for the uncertainty associated to this decision-making step, an interval type-2 fuzzy membership function composed of an optimistic/upper component and a pessimistic/lower component is used. The final class attribution employs a probabilistic method for interval comparison. Evaluation results obtained after defuzzification show that, with a careful parameter setting, the proposed membership function effectively improves the performance of the baseline autoencoder, and performs better than the state-of-the-art one-class SVM in anomaly detection.

Copyright
© 2021, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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Volume Title
Joint Proceedings of the 19th World Congress of the International Fuzzy Systems Association (IFSA), the 12th Conference of the European Society for Fuzzy Logic and Technology (EUSFLAT), and the 11th International Summer School on Aggregation Operators (AGOP)
Series
Atlantis Studies in Uncertainty Modelling
Publication Date
30 August 2021
ISBN
978-94-6239-423-0
ISSN
2589-6644
DOI
10.2991/asum.k.210827.059How to use a DOI?
Copyright
© 2021, the Authors. Published by Atlantis Press.
Open Access
This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Cite this article

risenwbib
TY  - CONF
AU  - Stefano Rovetta
AU  - Zied Mnasri
AU  - Francesco Masulli
AU  - Alberto Cabri
PY  - 2021
DA  - 2021/08/30
TI  - Audio Surveillance of Road Traffic: An Approach Based on Anomaly Detection and Interval Type-2 Fuzzy Sets
BT  - Joint Proceedings of the 19th World Congress of the International Fuzzy Systems Association (IFSA), the 12th Conference of the European Society for Fuzzy Logic and Technology (EUSFLAT), and the 11th International Summer School on Aggregation Operators (AGOP)
PB  - Atlantis Press
SP  - 443
EP  - 451
SN  - 2589-6644
UR  - https://doi.org/10.2991/asum.k.210827.059
DO  - 10.2991/asum.k.210827.059
ID  - Rovetta2021
ER  -