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  1. A500 情報学部/情報学研究科・情報文化学部・情報科学研究科
  2. A500e 会議資料
  3. 国際会議

A Browsing and Retrieval System for Driving Data

http://hdl.handle.net/2237/14602
http://hdl.handle.net/2237/14602
c5e7e20b-d908-423e-acf3-3c6d6b038837
名前 / ファイル ライセンス アクション
1055.pdf 1055.pdf (366.2 kB)
Item type 学術雑誌論文 / Journal Article(1)
公開日 2011-04-19
タイトル
タイトル A Browsing and Retrieval System for Driving Data
言語 en
著者 Naito, Masashi

× Naito, Masashi

WEKO 39924

en Naito, Masashi

Search repository
Miyajima, Chiyomi

× Miyajima, Chiyomi

WEKO 39925

en Miyajima, Chiyomi

Search repository
Nishino, Takanori

× Nishino, Takanori

WEKO 39926

en Nishino, Takanori

Search repository
Kitaoka, Norihide

× Kitaoka, Norihide

WEKO 39927

en Kitaoka, Norihide

Search repository
Takeda, Kazuya

× Takeda, Kazuya

WEKO 39928

en Takeda, Kazuya

Search repository
アクセス権
アクセス権 open access
アクセス権URI http://purl.org/coar/access_right/c_abf2
権利
言語 en
権利情報 © 2010 IEEE. Reprinted, with permission, from Masashi Naito; Chiyomi Miyajima; Takanori Nishino; Norihide Kitaoka; Kazuya Takeda, A Browsing and Retrieval System for Driving Data, Intelligent Vehicles Symposium (IV), 2010 IEEE, Jun/2010
抄録
内容記述 With the increased presence and recent advances of drive recorders, rich driving data that include video, vehicle acceleration signals, driver speech, GPS data, and several sensor signals can be continuously recorded and stored. These advances enable researchers to study driving behavior more extensively for traffic safety. However, increasing the variety and the amount of driving data complicates the simultaneous browsing of various data and finding desired data from large databases. In this study, we develop a browsing and retrieval system for driving data that provides a multi-modal data browser, query- and similarity-based retrieval functions, and a fast browsing function that skips redundant scenes. For sharing data with several users, this system can be used via networks from PCs or smartphones, This system uses a time-series active search, which has been successfully used for fast search of audio and video data, as its retrieval function algorithm. In a few seconds, this system can retrieve driving scenes that are similar to an input scene from 80,000 scenes. Retrieval performance was compared in various retrieval conditions by changing the codebook size of the vector quantization for the histogram features and a combination of driving signals. Experimental results showed that more than 97% retrieval performance was achieved for driving behaviors of left/right turns and curves using a combination of such complementary information as steering angles and lateral acceleration. We also compared the proposed method to a conventional image-based retrieval method using subjective similarity scores of driving scenes. Our proposed system retrieved similar scenes with about a 75% retrieval performance that was five points higher than a conventional image-based retrieval method. It is because image-based method is sensitive to changes of image in the area except in the region of interest for driving data retrieval. The fast browsing function also skipped scenes that could not be skipped by an image-based method.
言語 en
内容記述タイプ Abstract
出版者
言語 en
出版者 IEEE
言語
言語 eng
資源タイプ
資源タイプresource http://purl.org/coar/resource_type/c_6501
タイプ journal article
出版タイプ
出版タイプ AM
出版タイプResource http://purl.org/coar/version/c_ab4af688f83e57aa
DOI
関連タイプ isVersionOf
識別子タイプ DOI
関連識別子 https://doi.org/10.1109/IVS.2010.5547999
ISBN
関連タイプ isPartOf
識別子タイプ ISBN
関連識別子 978-1-4244-7866-8
ISSN
収録物識別子タイプ PISSN
収録物識別子 1931-0587
書誌情報 en : IEEE Intelligent Vehicles Symposium (IV)

p. 1159-1165, 発行日 2010-06-21
著者版フラグ
値 author
URI
識別子 http://dx.doi.org/10.1109/IVS.2010.5547999
識別子タイプ DOI
URI
識別子 http://hdl.handle.net/2237/14602
識別子タイプ HDL
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