Robust visual voice activity detection using local variance histogram in vehicular environments

Kyungsun Lee; Taeyup Song; Sungsoo Kim; David K. Han; Hanseok Ko

doi:10.1109/ICCE.2015.7066482

Robust visual voice activity detection using local variance histogram in vehicular environments

Kyungsun Lee, Taeyup Song, Sungsoo Kim, David K. Han, Hanseok Ko

School of Electrical Engineering

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

In this paper, a Vision based Voice Activity Detection (VVAD) algorithm is proposed using Local Variance Histogram (LVH). In conventional VVAD algorithm, the motion measure such as optical flow and intensity histogram are widely used. However, this approach is unstable under varying illumination and global motion changes which frequently occur in moving vehicular environment. To mitigate this problem, an appropriate framework based on LVH feature is developed. Comparison with two other conventional visual voice activity detectors shows the proposed method to be consistently more accurate and yields a substantial improvement in terms of detection probability and false alarm rate.

Original language	English
Title of host publication	2015 IEEE International Conference on Consumer Electronics, ICCE 2015
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	449-450
Number of pages	2
ISBN (Electronic)	9781479975426
DOIs	https://doi.org/10.1109/ICCE.2015.7066482
Publication status	Published - 2015 Mar 23
Event	2015 IEEE International Conference on Consumer Electronics, ICCE 2015 - Las Vegas, United States Duration: 2015 Jan 9 → 2015 Jan 12

Publication series

Name	2015 IEEE International Conference on Consumer Electronics, ICCE 2015

Other

Other	2015 IEEE International Conference on Consumer Electronics, ICCE 2015
Country/Territory	United States
City	Las Vegas
Period	15/1/9 → 15/1/12

ASJC Scopus subject areas

Computer Networks and Communications
Electrical and Electronic Engineering
Industrial and Manufacturing Engineering

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10.1109/ICCE.2015.7066482

Cite this

Lee, K., Song, T., Kim, S., Han, D. K., & Ko, H. (2015). Robust visual voice activity detection using local variance histogram in vehicular environments. In 2015 IEEE International Conference on Consumer Electronics, ICCE 2015 (pp. 449-450). Article 7066482 (2015 IEEE International Conference on Consumer Electronics, ICCE 2015). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICCE.2015.7066482

Robust visual voice activity detection using local variance histogram in vehicular environments. / Lee, Kyungsun; Song, Taeyup; Kim, Sungsoo et al.
2015 IEEE International Conference on Consumer Electronics, ICCE 2015. Institute of Electrical and Electronics Engineers Inc., 2015. p. 449-450 7066482 (2015 IEEE International Conference on Consumer Electronics, ICCE 2015).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Lee, K, Song, T, Kim, S, Han, DK & Ko, H 2015, Robust visual voice activity detection using local variance histogram in vehicular environments. in 2015 IEEE International Conference on Consumer Electronics, ICCE 2015., 7066482, 2015 IEEE International Conference on Consumer Electronics, ICCE 2015, Institute of Electrical and Electronics Engineers Inc., pp. 449-450, 2015 IEEE International Conference on Consumer Electronics, ICCE 2015, Las Vegas, United States, 15/1/9. https://doi.org/10.1109/ICCE.2015.7066482

Lee K, Song T, Kim S, Han DK, Ko H. Robust visual voice activity detection using local variance histogram in vehicular environments. In 2015 IEEE International Conference on Consumer Electronics, ICCE 2015. Institute of Electrical and Electronics Engineers Inc. 2015. p. 449-450. 7066482. (2015 IEEE International Conference on Consumer Electronics, ICCE 2015). doi: 10.1109/ICCE.2015.7066482

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abstract = "In this paper, a Vision based Voice Activity Detection (VVAD) algorithm is proposed using Local Variance Histogram (LVH). In conventional VVAD algorithm, the motion measure such as optical flow and intensity histogram are widely used. However, this approach is unstable under varying illumination and global motion changes which frequently occur in moving vehicular environment. To mitigate this problem, an appropriate framework based on LVH feature is developed. Comparison with two other conventional visual voice activity detectors shows the proposed method to be consistently more accurate and yields a substantial improvement in terms of detection probability and false alarm rate.",

author = "Kyungsun Lee and Taeyup Song and Sungsoo Kim and Han, {David K.} and Hanseok Ko",

note = "Publisher Copyright: {\textcopyright} 2015 IEEE. Copyright: Copyright 2015 Elsevier B.V., All rights reserved.; 2015 IEEE International Conference on Consumer Electronics, ICCE 2015 ; Conference date: 09-01-2015 Through 12-01-2015",

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N2 - In this paper, a Vision based Voice Activity Detection (VVAD) algorithm is proposed using Local Variance Histogram (LVH). In conventional VVAD algorithm, the motion measure such as optical flow and intensity histogram are widely used. However, this approach is unstable under varying illumination and global motion changes which frequently occur in moving vehicular environment. To mitigate this problem, an appropriate framework based on LVH feature is developed. Comparison with two other conventional visual voice activity detectors shows the proposed method to be consistently more accurate and yields a substantial improvement in terms of detection probability and false alarm rate.

AB - In this paper, a Vision based Voice Activity Detection (VVAD) algorithm is proposed using Local Variance Histogram (LVH). In conventional VVAD algorithm, the motion measure such as optical flow and intensity histogram are widely used. However, this approach is unstable under varying illumination and global motion changes which frequently occur in moving vehicular environment. To mitigate this problem, an appropriate framework based on LVH feature is developed. Comparison with two other conventional visual voice activity detectors shows the proposed method to be consistently more accurate and yields a substantial improvement in terms of detection probability and false alarm rate.

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Robust visual voice activity detection using local variance histogram in vehicular environments

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