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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. A500a 雑誌掲載論文
  3. 学術雑誌

頭部姿勢を考慮した視線方向推定に関する検討

http://hdl.handle.net/2237/23860
35330894-04ea-4b50-a99c-9366c8d1917c
名前 / ファイル ライセンス アクション
110009713422.pdf 110009713422.pdf (919.4 kB)
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 頭部姿勢を考慮した視線方向推定に関する検討
その他のタイトル
その他のタイトル A Study on Gaze Estimation from Person Images Using Head Pose Information
著者 船津, 暢宏

× 船津, 暢宏

WEKO 64437

船津, 暢宏

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高橋, 友和

× 高橋, 友和

WEKO 64438

高橋, 友和

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出口, 大輔

× 出口, 大輔

WEKO 64439

出口, 大輔

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井手, 一郎

× 井手, 一郎

WEKO 64440

井手, 一郎

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村瀬, 洋

× 村瀬, 洋

WEKO 64441

村瀬, 洋

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FUNATSU, Nobuhiro

× FUNATSU, Nobuhiro

WEKO 64442

FUNATSU, Nobuhiro

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TAKAHASHI, Tomokazu

× TAKAHASHI, Tomokazu

WEKO 64443

TAKAHASHI, Tomokazu

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DEGUCHI, Daisuke

× DEGUCHI, Daisuke

WEKO 64444

DEGUCHI, Daisuke

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IDE, Ichiro

× IDE, Ichiro

WEKO 64445

IDE, Ichiro

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MURASE, Hiroshi

× MURASE, Hiroshi

WEKO 64446

MURASE, Hiroshi

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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 視線方向推定
キーワード
主題Scheme Other
主題 顔の向き推定
キーワード
主題Scheme Other
主題 gaze estimation
キーワード
主題Scheme Other
主題 face direction estimation
抄録
内容記述 近年,カメラを用いて人物の視線方向を推定する技術が注目されている.しかし,実環境下で得られる人物画像は,低解像度であるほか,遮蔽や照明変化などを含むことが多く,高品質な目領域画像を必要とする従来手法の適用は難しい.そこで本研究では,体に対する顔の向きと顔の動きから視線方向を推定する手法を提案する.提案手法では,まず人物動画像から姿勢情報を推定し,その結果に基づいて視線方向の尤度関数を計算する.そして,尤度が最大となる視線方向を推定結果として出力する.評価実験において,提案手法と従来手法の視線推定誤差を比較することにより,提案手法の有効性を確認した. Gaze estimation techniques using a camera have widely been studied in recent years. Most existing methods require a high-quality image of the eye area. However, an eye image obtained under real environments is often in low resolution, affected by illumination changes, and occluded by sunglasses or head rotation. Thus, we propose a method that estimates a gaze direction accurately using pose information including the head direction, the body direction, and the head motion. The proposed method estimates the pose information from an input person image sequence. Then, it calculates a likelihood function of gaze directions using the estimated pose information. Finally, it outputs the gaze direction that maximizes the likelihood value as a gaze estimation result. Experimental results showed that the proposed method could estimate gaze directions more accurately than an existing method. This indicates the effectiveness of the proposed method.
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 112, 号 495, p. 99-104, 発行日 2013-03
著者版フラグ
値 publisher
シリーズ
関連名称
関連名称 IEICE Technical Report;PRMU2012-197
URI
識別子 http://ci.nii.ac.jp/naid/110009713422/
識別子タイプ URI
URI
識別子 http://hdl.handle.net/2237/23860
識別子タイプ HDL
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