Presentation | 2003/5/22 Recognition of Sound of Moving Vehicles Using HMM Composition Yoshitaka HIRAMATSU, Jien KATO, Toyohide WATANABE, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | With a view of estimating traffic density, this paper proposes a hidden Markov model that recognizes the sound of moving cars on a single lane as an alternative means to image processing, in case vehicle detection through images is not available (such as at night). This model is supposed applicable to recognizing the sound mixed by three or less neighboring moving vehicles. It is generated using HMM composition method: firstly, an HMM with four states is produced for recognizing one moving car, then three states of the HMM are chosen and their transition probabilities are composed to generate the model which is able to recognize the mixed sound from moving cars up to three. Some experiments applying this model to practical traffic data have been performed to verify the model effectiveness. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | HMM / vehicle sound / vehicle detection |
Paper # | PRMU2003-7 |
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Committee | PRMU |
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Conference Date | 2003/5/22(1days) |
Place (in Japanese) | (See Japanese page) |
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Registration To | Pattern Recognition and Media Understanding (PRMU) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Recognition of Sound of Moving Vehicles Using HMM Composition |
Sub Title (in English) | |
Keyword(1) | HMM |
Keyword(2) | vehicle sound |
Keyword(3) | vehicle detection |
1st Author's Name | Yoshitaka HIRAMATSU |
1st Author's Affiliation | Graduate School of Engineering, Nagoya University() |
2nd Author's Name | Jien KATO |
2nd Author's Affiliation | Graduate School of Information Science, Nagoya University |
3rd Author's Name | Toyohide WATANABE |
3rd Author's Affiliation | Graduate School of Information Science, Nagoya University |
Date | 2003/5/22 |
Paper # | PRMU2003-7 |
Volume (vol) | vol.103 |
Number (no) | 95 |
Page | pp.pp.- |
#Pages | 6 |
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