Cascade classifiers trained on gammatonegrams for reliably detecting audio events

Pasquale Foggia; Alessia Saggese; Nicola Strisciuglio; Mario Vento

doi:10.1109/AVSS.2014.6918643

Cascade classifiers trained on gammatonegrams for reliably detecting audio events

Pasquale Foggia^*
, Alessia Saggese
, Nicola Strisciuglio
, Mario Vento

^*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

23 Citations (Scopus)

Abstract

In this paper we propose a novel method for the detection of events of interest through audio analysis. The system that we propose is based on the representation of the audio streams through a Gammatone image, which describes the time-frequency distribution of the energy of the signal; this representation is inspired by the functioning of the human auditory system. A pool of AdaBoost cascade classifiers, one for each class of events of interest, is involved in the event detection stage. The performance of the proposed system has been evaluated on a large data set of audio events for surveillance applications and the achieved results, compared with two state of the art approaches, confirm its effectiveness.

Original language	English
Title of host publication	11th IEEE International Conference on Advanced Video and Signal-Based Surveillance, AVSS 2014
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	50-55
Number of pages	6
ISBN (Electronic)	9781479948710
DOIs	https://doi.org/10.1109/AVSS.2014.6918643
Publication status	Published - 1-Jan-2014
Externally published	Yes
Event	11th IEEE International Conference on Advanced Video and Signal-Based Surveillance, AVSS 2014 - Seoul, Korea, Republic of Duration: 26-Aug-2014 → 29-Aug-2014

Conference

Conference	11th IEEE International Conference on Advanced Video and Signal-Based Surveillance, AVSS 2014
Country/Territory	Korea, Republic of
City	Seoul
Period	26/08/2014 → 29/08/2014

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@inproceedings{e43ed3f159504c4d93312b5309c7e6dc,

title = "Cascade classifiers trained on gammatonegrams for reliably detecting audio events",

abstract = "In this paper we propose a novel method for the detection of events of interest through audio analysis. The system that we propose is based on the representation of the audio streams through a Gammatone image, which describes the time-frequency distribution of the energy of the signal; this representation is inspired by the functioning of the human auditory system. A pool of AdaBoost cascade classifiers, one for each class of events of interest, is involved in the event detection stage. The performance of the proposed system has been evaluated on a large data set of audio events for surveillance applications and the achieved results, compared with two state of the art approaches, confirm its effectiveness.",

author = "Pasquale Foggia and Alessia Saggese and Nicola Strisciuglio and Mario Vento",

year = "2014",

month = jan,

day = "1",

doi = "10.1109/AVSS.2014.6918643",

language = "English",

pages = "50--55",

booktitle = "11th IEEE International Conference on Advanced Video and Signal-Based Surveillance, AVSS 2014",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

note = "11th IEEE International Conference on Advanced Video and Signal-Based Surveillance, AVSS 2014 ; Conference date: 26-08-2014 Through 29-08-2014",

}

Foggia, P, Saggese, A, Strisciuglio, N & Vento, M 2014, Cascade classifiers trained on gammatonegrams for reliably detecting audio events. in 11th IEEE International Conference on Advanced Video and Signal-Based Surveillance, AVSS 2014., 6918643, Institute of Electrical and Electronics Engineers Inc., pp. 50-55, 11th IEEE International Conference on Advanced Video and Signal-Based Surveillance, AVSS 2014, Seoul, Korea, Republic of, 26/08/2014. https://doi.org/10.1109/AVSS.2014.6918643

Cascade classifiers trained on gammatonegrams for reliably detecting audio events. / Foggia, Pasquale; Saggese, Alessia; Strisciuglio, Nicola et al.
11th IEEE International Conference on Advanced Video and Signal-Based Surveillance, AVSS 2014. Institute of Electrical and Electronics Engineers Inc., 2014. p. 50-55 6918643.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

TY - GEN

T1 - Cascade classifiers trained on gammatonegrams for reliably detecting audio events

AU - Foggia, Pasquale

AU - Saggese, Alessia

AU - Strisciuglio, Nicola

AU - Vento, Mario

PY - 2014/1/1

Y1 - 2014/1/1

N2 - In this paper we propose a novel method for the detection of events of interest through audio analysis. The system that we propose is based on the representation of the audio streams through a Gammatone image, which describes the time-frequency distribution of the energy of the signal; this representation is inspired by the functioning of the human auditory system. A pool of AdaBoost cascade classifiers, one for each class of events of interest, is involved in the event detection stage. The performance of the proposed system has been evaluated on a large data set of audio events for surveillance applications and the achieved results, compared with two state of the art approaches, confirm its effectiveness.

AB - In this paper we propose a novel method for the detection of events of interest through audio analysis. The system that we propose is based on the representation of the audio streams through a Gammatone image, which describes the time-frequency distribution of the energy of the signal; this representation is inspired by the functioning of the human auditory system. A pool of AdaBoost cascade classifiers, one for each class of events of interest, is involved in the event detection stage. The performance of the proposed system has been evaluated on a large data set of audio events for surveillance applications and the achieved results, compared with two state of the art approaches, confirm its effectiveness.

UR - https://www.scopus.com/pages/publications/84909953241

U2 - 10.1109/AVSS.2014.6918643

DO - 10.1109/AVSS.2014.6918643

M3 - Conference contribution

AN - SCOPUS:84909953241

SP - 50

EP - 55

BT - 11th IEEE International Conference on Advanced Video and Signal-Based Surveillance, AVSS 2014

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 11th IEEE International Conference on Advanced Video and Signal-Based Surveillance, AVSS 2014

Y2 - 26 August 2014 through 29 August 2014

ER -

Cascade classifiers trained on gammatonegrams for reliably detecting audio events

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