ログイン
言語:

WEKO3

  • トップ
  • コミュニティ
  • ランキング
AND
To
lat lon distance
To

Field does not validate



インデックスリンク

インデックスツリー

メールアドレスを入力してください。

WEKO

One fine body…

WEKO

One fine body…

アイテム

{"_buckets": {"deposit": "53312ef8-5f32-4265-b20c-5f523cd8629d"}, "_deposit": {"id": "21704", "owners": [], "pid": {"revision_id": 0, "type": "depid", "value": "21704"}, "status": "published"}, "_oai": {"id": "oai:nagoya.repo.nii.ac.jp:00021704"}, "item_10_alternative_title_19": {"attribute_name": "\u305d\u306e\u4ed6\u306e\u8a00\u8a9e\u306e\u30bf\u30a4\u30c8\u30eb", "attribute_value_mlt": [{"subitem_alternative_title": "Prediction of driving behavior using driver\u0027s gaze information"}]}, "item_10_biblio_info_6": {"attribute_name": "\u66f8\u8a8c\u60c5\u5831", "attribute_value_mlt": [{"bibliographicIssueDates": {"bibliographicIssueDate": "2011-05-12", "bibliographicIssueDateType": "Issued"}, "bibliographicIssueNumber": "48", "bibliographicPageEnd": "110", "bibliographicPageStart": "105", "bibliographicVolumeNumber": "111", "bibliographic_titles": [{"bibliographic_title": "\u96fb\u5b50\u60c5\u5831\u901a\u4fe1\u5b66\u4f1a\u6280\u8853\u7814\u7a76\u5831\u544a. PRMU, \u30d1\u30bf\u30fc\u30f3\u8a8d\u8b58\u30fb\u30e1\u30c7\u30a3\u30a2\u7406\u89e3"}]}]}, "item_10_description_4": {"attribute_name": "\u6284\u9332", "attribute_value_mlt": [{"subitem_description": "\u8fd1\u5e74,\u904b\u8ee2\u884c\u52d5\u4e88\u6e2c\u306b\u57fa\u3065\u304f\u5b89\u5168\u904b\u8ee2\u652f\u63f4\u304c\u5f37\u304f\u6c42\u3081\u3089\u308c\u3066\u3044\u308b.\u4e00\u822c\u7684\u306b\u30c9\u30e9\u30a4\u30d0\u306f,\u8a8d\u77e5\u30fb\u5224\u65ad\u30fb\u64cd\u4f5c\u306e\u624b\u9806\u3092\u8e0f\u307f\u81ea\u52d5\u8eca\u3092\u904b\u8ee2\u3059\u308b.\u30c9\u30e9\u30a4\u30d0\u306f\u4e3b\u306b\u8996\u899a\u304b\u3089\u306e\u60c5\u5831\u306b\u3088\u308a\u5916\u754c\u3092\u8a8d\u77e5\u3059\u308b\u305f\u3081,\u8a8d\u77e5\u306e\u6bb5\u968e\u306b\u6df1\u304f\u95a2\u308f\u3063\u3066\u3044\u308b\u8996\u7dda\u60c5\u5831\u306f,\u8eca\u4e21\u60c5\u5831\u306b\u5148\u884c\u3057\u3066\u60c5\u5831\u304c\u5f97\u3089\u308c\u308b.\u305d\u3053\u3067\u672c\u7814\u7a76\u3067\u306f,\u30c9\u30e9\u30a4\u30d0\u306e\u8996\u7dda\u60c5\u5831\u3092\u5229\u7528\u3057,\u904b\u8ee2\u884c\u52d5\u3092\u4e88\u6e2c\u3059\u308b\u624b\u6cd5\u3092\u63d0\u6848\u3059\u308b.\u4e88\u6e2c\u5bfe\u8c61\u3068\u3057\u305f\u904b\u8ee2\u884c\u52d5\u306f,\u5de6\u6298,\u53f3\u6298,\u5de6\u8eca\u7dda\u5909\u66f4,\u53f3\u8eca\u7dda\u5909\u66f4,\u4fe1\u53f7\u76f4\u9032,\u4fe1\u53f7\u505c\u6b62\u306e6\u7a2e\u985e\u3067\u3042\u308b.\u63d0\u6848\u624b\u6cd5\u306f,\u5b66\u7fd2\u6bb5\u968e\u3068\u4e88\u6e2c\u6bb5\u968e\u306e2\u6bb5\u968e\u306b\u5206\u3051\u3089\u308c\u308b.\u5b66\u7fd2\u6bb5\u968e\u3067\u306f,\u5404\u904b\u8ee2\u884c\u52d5\u304c\u8d77\u304d\u308b\u524d\u306e\u8996\u7dda\u60c5\u5831\u304b\u3089\u4e88\u6e2c\u306b\u5229\u7528\u3067\u304d\u308b\u7279\u5fb4\u3092\u62bd\u51fa\u3057,\u4e8b\u524d\u306b\u5b66\u7fd2\u3092\u884c\u3046.\u305d\u3057\u3066,\u4e88\u6e2c\u5bfe\u8c61\u3067\u3042\u308b\u8996\u7dda\u60c5\u5831\u304b\u3089,\u5b66\u7fd2\u6bb5\u968e\u3068\u540c\u69d8\u306b\u3057\u3066\u7279\u5fb4\u3092\u62bd\u51fa\u3057,\u5404\u7279\u5fb4\u3092\u5b66\u7fd2\u3057\u305fSVM\u306b\u3088\u308a\u904b\u8ee2\u884c\u52d5\u4e88\u6e2c\u3092\u884c\u3046.\u5b9f\u969b\u306b\u4e00\u822c\u9053\u3092\u8d70\u884c\u3057\u3066\u53d6\u5f97\u3057\u305f\u8996\u7dda\u30c7\u30fc\u30bf\u3092\u7528\u3044\u3066\u8a55\u4fa1\u5b9f\u9a13\u3092\u884c\u3044,\u63d0\u6848\u624b\u6cd5\u306e\u6709\u52b9\u6027\u3092\u78ba\u8a8d\u3057\u305f.In recent years, driving assistance systems based on the prediction of driving behavior are becoming important for safe driving. A driver typically drives a vehicle following the procedure of recognition, decision and operation. Because a driver mainly recognizes the outside world from visual information, the gaze information will reflect the driver\u0027s behavior earlier than the information obtained from the vehicle. Therefore, we propose a method of predicting a driving behavior using the driver\u0027s gaze information. This method tries to predict six behaviors: left turn, right turn, lane change from right to left, lane change from left to right, going straight at a traffic intersection and stopping for a red light. The proposed method consists of two phases, namely, learning phase and predicting phase. In the learning phase, the method extracts features from gaze information and constructs a SVM classifier. Then, the method extracts the features from gaze information during driving, and predict the driving behavior using the constructed classifier. We evaluated the method with the gaze information obtained on an open road, and we confirmed its effectiveness. [Note] This document is an informal handout distributed at an IEICE TC-PRMU workshop.", "subitem_description_type": "Abstract"}]}, "item_10_identifier_60": {"attribute_name": "URI", "attribute_value_mlt": [{"subitem_identifier_type": "URI", "subitem_identifier_uri": "http://ci.nii.ac.jp/naid/110008726271/"}, {"subitem_identifier_type": "HDL", "subitem_identifier_uri": "http://hdl.handle.net/2237/23853"}]}, "item_10_publisher_32": {"attribute_name": "\u51fa\u7248\u8005", "attribute_value_mlt": [{"subitem_publisher": "\u4e00\u822c\u793e\u56e3\u6cd5\u4eba\u96fb\u5b50\u60c5\u5831\u901a\u4fe1\u5b66\u4f1a"}]}, "item_10_relation_40": {"attribute_name": "\u30b7\u30ea\u30fc\u30ba", "attribute_value_mlt": [{"subitem_relation_name": [{"subitem_relation_name_text": "IEICE Technical Report;IE2011-27, PRMU2011-19, MI2011-19"}]}]}, "item_10_rights_12": {"attribute_name": "\u6a29\u5229", "attribute_value_mlt": [{"subitem_rights": "(c)\u4e00\u822c\u793e\u56e3\u6cd5\u4eba\u96fb\u5b50\u60c5\u5831\u901a\u4fe1\u5b66\u4f1a \u672c\u6587\u30c7\u30fc\u30bf\u306f\u5b66\u5354\u4f1a\u306e\u8a31\u8afe\u306b\u57fa\u3065\u304dCiNii\u304b\u3089\u8907\u88fd\u3057\u305f\u3082\u306e\u3067\u3042\u308b"}]}, "item_10_select_15": {"attribute_name": "\u8457\u8005\u7248\u30d5\u30e9\u30b0", "attribute_value_mlt": [{"subitem_select_item": "publisher"}]}, "item_10_source_id_7": {"attribute_name": "ISSN", "attribute_value_mlt": [{"subitem_source_identifier": "0913-5685", "subitem_source_identifier_type": "ISSN"}]}, "item_creator": {"attribute_name": "\u8457\u8005", "attribute_type": "creator", "attribute_value_mlt": [{"creatorNames": [{"creatorName": "\u4e0a\u5742, \u7adc\u898f"}], "nameIdentifiers": [{"nameIdentifier": "64345", "nameIdentifierScheme": "WEKO"}]}, {"creatorNames": [{"creatorName": "\u91ce\u7530, \u96c5\u6587"}], "nameIdentifiers": [{"nameIdentifier": "64346", "nameIdentifierScheme": "WEKO"}]}, {"creatorNames": [{"creatorName": "\u76ee\u52a0\u7530, \u6176\u4eba"}], "nameIdentifiers": [{"nameIdentifier": "64347", "nameIdentifierScheme": "WEKO"}]}, {"creatorNames": [{"creatorName": "\u51fa\u53e3, \u5927\u8f14"}], "nameIdentifiers": [{"nameIdentifier": "64348", "nameIdentifierScheme": "WEKO"}]}, {"creatorNames": [{"creatorName": "\u4e95\u624b, \u4e00\u90ce"}], "nameIdentifiers": [{"nameIdentifier": "64349", "nameIdentifierScheme": "WEKO"}]}, {"creatorNames": [{"creatorName": "\u6751\u702c, \u6d0b"}], "nameIdentifiers": [{"nameIdentifier": "64350", "nameIdentifierScheme": "WEKO"}]}, {"creatorNames": [{"creatorName": "KAMISAKA, Tatsuki"}], "nameIdentifiers": [{"nameIdentifier": "64351", "nameIdentifierScheme": "WEKO"}]}, {"creatorNames": [{"creatorName": "NODA, Masafumi"}], "nameIdentifiers": [{"nameIdentifier": "64352", "nameIdentifierScheme": "WEKO"}]}, {"creatorNames": [{"creatorName": "MEKADA, Yoshito"}], "nameIdentifiers": [{"nameIdentifier": "64353", "nameIdentifierScheme": "WEKO"}]}, {"creatorNames": [{"creatorName": "DEGUCHI, Daisuke"}], "nameIdentifiers": [{"nameIdentifier": "64354", "nameIdentifierScheme": "WEKO"}]}, {"creatorNames": [{"creatorName": "IDE, Ichiro"}], "nameIdentifiers": [{"nameIdentifier": "64355", "nameIdentifierScheme": "WEKO"}]}, {"creatorNames": [{"creatorName": "MURASE, Hiroshi"}], "nameIdentifiers": [{"nameIdentifier": "64356", "nameIdentifierScheme": "WEKO"}]}]}, "item_files": {"attribute_name": "\u30d5\u30a1\u30a4\u30eb\u60c5\u5831", "attribute_type": "file", "attribute_value_mlt": [{"accessrole": "open_date", "date": [{"dateType": "Available", "dateValue": "2018-02-21"}], "displaytype": "detail", "download_preview_message": "", "file_order": 0, "filename": "110008726271.pdf", "filesize": [{"value": "1.1 MB"}], "format": "application/pdf", "future_date_message": "", "is_thumbnail": false, "licensetype": "license_free", "mimetype": "application/pdf", "size": 1100000.0, "url": {"label": "110008726271.pdf", "url": "https://nagoya.repo.nii.ac.jp/record/21704/files/110008726271.pdf"}, "version_id": "1c887982-92aa-40dc-984f-8b95800a258a"}]}, "item_keyword": {"attribute_name": "\u30ad\u30fc\u30ef\u30fc\u30c9", "attribute_value_mlt": [{"subitem_subject": "\u904b\u8ee2\u884c\u52d5\u4e88\u6e2c", "subitem_subject_scheme": "Other"}, {"subitem_subject": "\u8996\u7dda\u60c5\u5831", "subitem_subject_scheme": "Other"}, {"subitem_subject": "Prediction of driving behavior", "subitem_subject_scheme": "Other"}, {"subitem_subject": "Gaze information", "subitem_subject_scheme": "Other"}]}, "item_language": {"attribute_name": "\u8a00\u8a9e", "attribute_value_mlt": [{"subitem_language": "jpn"}]}, "item_resource_type": {"attribute_name": "\u8cc7\u6e90\u30bf\u30a4\u30d7", "attribute_value_mlt": [{"resourcetype": "journal article", "resourceuri": "http://purl.org/coar/resource_type/c_6501"}]}, "item_title": "\u30c9\u30e9\u30a4\u30d0\u306e\u8996\u7dda\u60c5\u5831\u3092\u5229\u7528\u3057\u305f\u904b\u8ee2\u884c\u52d5\u4e88\u6e2c(\u4e00\u822c\u30bb\u30c3\u30b7\u30e7\u30f3,\u533b\u7528\u753b\u50cf\u51e6\u7406\u5206\u91ce\u306b\u304a\u3051\u308b\u8a08\u6e2c\u30fb\u8a8d\u8b58\u30fb\u7406\u89e3)", "item_titles": {"attribute_name": "\u30bf\u30a4\u30c8\u30eb", "attribute_value_mlt": [{"subitem_title": "\u30c9\u30e9\u30a4\u30d0\u306e\u8996\u7dda\u60c5\u5831\u3092\u5229\u7528\u3057\u305f\u904b\u8ee2\u884c\u52d5\u4e88\u6e2c(\u4e00\u822c\u30bb\u30c3\u30b7\u30e7\u30f3,\u533b\u7528\u753b\u50cf\u51e6\u7406\u5206\u91ce\u306b\u304a\u3051\u308b\u8a08\u6e2c\u30fb\u8a8d\u8b58\u30fb\u7406\u89e3)"}]}, "item_type_id": "10", "owner": "1", "path": ["312/313/314"], "permalink_uri": "http://hdl.handle.net/2237/23853", "pubdate": {"attribute_name": "\u516c\u958b\u65e5", "attribute_value": "2016-03-16"}, "publish_date": "2016-03-16", "publish_status": "0", "recid": "21704", "relation": {}, "relation_version_is_last": true, "title": ["\u30c9\u30e9\u30a4\u30d0\u306e\u8996\u7dda\u60c5\u5831\u3092\u5229\u7528\u3057\u305f\u904b\u8ee2\u884c\u52d5\u4e88\u6e2c(\u4e00\u822c\u30bb\u30c3\u30b7\u30e7\u30f3,\u533b\u7528\u753b\u50cf\u51e6\u7406\u5206\u91ce\u306b\u304a\u3051\u308b\u8a08\u6e2c\u30fb\u8a8d\u8b58\u30fb\u7406\u89e3)"], "weko_shared_id": null}
  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. A500a 雑誌掲載論文
  3. 学術雑誌

ドライバの視線情報を利用した運転行動予測(一般セッション,医用画像処理分野における計測・認識・理解)

http://hdl.handle.net/2237/23853
3e6439ca-4b17-4fac-a0eb-5ec39b25a44d
名前 / ファイル ライセンス アクション
110008726271.pdf 110008726271.pdf (1.1 MB)
Item type 学術雑誌論文 / Journal Article(1)
公開日 2016-03-16
タイトル
タイトル ドライバの視線情報を利用した運転行動予測(一般セッション,医用画像処理分野における計測・認識・理解)
その他のタイトル
その他のタイトル Prediction of driving behavior using driver's gaze information
著者 上坂, 竜規

× 上坂, 竜規

WEKO 64345

上坂, 竜規

Search repository
野田, 雅文

× 野田, 雅文

WEKO 64346

野田, 雅文

Search repository
目加田, 慶人

× 目加田, 慶人

WEKO 64347

目加田, 慶人

Search repository
出口, 大輔

× 出口, 大輔

WEKO 64348

出口, 大輔

Search repository
井手, 一郎

× 井手, 一郎

WEKO 64349

井手, 一郎

Search repository
村瀬, 洋

× 村瀬, 洋

WEKO 64350

村瀬, 洋

Search repository
KAMISAKA, Tatsuki

× KAMISAKA, Tatsuki

WEKO 64351

KAMISAKA, Tatsuki

Search repository
NODA, Masafumi

× NODA, Masafumi

WEKO 64352

NODA, Masafumi

Search repository
MEKADA, Yoshito

× MEKADA, Yoshito

WEKO 64353

MEKADA, Yoshito

Search repository
DEGUCHI, Daisuke

× DEGUCHI, Daisuke

WEKO 64354

DEGUCHI, Daisuke

Search repository
IDE, Ichiro

× IDE, Ichiro

WEKO 64355

IDE, Ichiro

Search repository
MURASE, Hiroshi

× MURASE, Hiroshi

WEKO 64356

MURASE, Hiroshi

Search repository
権利
権利情報 (c)一般社団法人電子情報通信学会 本文データは学協会の許諾に基づきCiNiiから複製したものである
キーワード
主題Scheme Other
主題 運転行動予測
キーワード
主題Scheme Other
主題 視線情報
キーワード
主題Scheme Other
主題 Prediction of driving behavior
キーワード
主題Scheme Other
主題 Gaze information
抄録
内容記述 近年,運転行動予測に基づく安全運転支援が強く求められている.一般的にドライバは,認知・判断・操作の手順を踏み自動車を運転する.ドライバは主に視覚からの情報により外界を認知するため,認知の段階に深く関わっている視線情報は,車両情報に先行して情報が得られる.そこで本研究では,ドライバの視線情報を利用し,運転行動を予測する手法を提案する.予測対象とした運転行動は,左折,右折,左車線変更,右車線変更,信号直進,信号停止の6種類である.提案手法は,学習段階と予測段階の2段階に分けられる.学習段階では,各運転行動が起きる前の視線情報から予測に利用できる特徴を抽出し,事前に学習を行う.そして,予測対象である視線情報から,学習段階と同様にして特徴を抽出し,各特徴を学習したSVMにより運転行動予測を行う.実際に一般道を走行して取得した視線データを用いて評価実験を行い,提案手法の有効性を確認した.In recent years, driving assistance systems based on the prediction of driving behavior are becoming important for safe driving. A driver typically drives a vehicle following the procedure of recognition, decision and operation. Because a driver mainly recognizes the outside world from visual information, the gaze information will reflect the driver's behavior earlier than the information obtained from the vehicle. Therefore, we propose a method of predicting a driving behavior using the driver's gaze information. This method tries to predict six behaviors: left turn, right turn, lane change from right to left, lane change from left to right, going straight at a traffic intersection and stopping for a red light. The proposed method consists of two phases, namely, learning phase and predicting phase. In the learning phase, the method extracts features from gaze information and constructs a SVM classifier. Then, the method extracts the features from gaze information during driving, and predict the driving behavior using the constructed classifier. We evaluated the method with the gaze information obtained on an open road, and we confirmed its effectiveness. [Note] This document is an informal handout distributed at an IEICE TC-PRMU workshop.
内容記述タイプ Abstract
出版者
出版者 一般社団法人電子情報通信学会
言語
言語 jpn
資源タイプ
資源タイプresource http://purl.org/coar/resource_type/c_6501
タイプ journal article
ISSN
収録物識別子タイプ ISSN
収録物識別子 0913-5685
書誌情報 電子情報通信学会技術研究報告. PRMU, パターン認識・メディア理解

巻 111, 号 48, p. 105-110, 発行日 2011-05-12
著者版フラグ
値 publisher
シリーズ
関連名称
関連名称 IEICE Technical Report;IE2011-27, PRMU2011-19, MI2011-19
URI
識別子 http://ci.nii.ac.jp/naid/110008726271/
識別子タイプ URI
URI
識別子 http://hdl.handle.net/2237/23853
識別子タイプ HDL
戻る
0
views
See details
Views

Versions

Ver.1 2021-03-01 15:15:20.537232
Show All versions

Share

Mendeley CiteULike Twitter Facebook Print Addthis

Cite as

Export

OAI-PMH
  • OAI-PMH JPCOAR
  • OAI-PMH DublinCore
  • OAI-PMH DDI
Other Formats
  • JSON
  • BIBTEX

Confirm


Powered by CERN Data Centre & Invenio


Powered by CERN Data Centre & Invenio