書誌事項
- タイトル別名
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- A Robust Gender and Age Estimation under Varying Facial Pose
- シセイ ヘンドウ ニ エイキョウサレナイ カオ ガゾウ カラノ セイベツ ネンレイ スイテイ
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This paper presents a method for gender and age estimation which is robust for facial pose changing. We propose a feature point detection method which is the Adapted Retinal Sampling Method (ARSM), and a feature extraction method. A basic concept of the ARSM is to add knowledge about the facial structure into the Retinal Sampling Method. In this method, feature points are detected based on 7 points corresponding to facial organ from face image. The reason why we used 7 points to basis of feature point detection is that facial organ is conspicuous in facial region, and it is comparatively easy to extract. As features which is robust for facial pose changing, a skin texture, a hue and a gabor jet are used for the gender and age estimation. For classification of gender and estimation of seriate age, we use a multi-layered neural network. Moreover, we examine the left-right symmetric property of the face concerning gender and age estimation by the proposed method.
収録刊行物
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- 電気学会論文誌Ｃ（電子・情報・システム部門誌）
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電気学会論文誌Ｃ（電子・情報・システム部門誌） 127 (7), 1022-1029, 2007
一般社団法人 電気学会
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詳細情報 詳細情報について
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- CRID
- 1390001204604503552
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- NII論文ID
- 10019522446
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- NII書誌ID
- AN10065950
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- ISSN
- 13488155
- 03854221
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- NDL書誌ID
- 8878712
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- 本文言語コード
- ja
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- データソース種別
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- JaLC
- NDL
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- CiNii Articles
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- 抄録ライセンスフラグ
- 使用不可