Appearance-based smile intensity estimation by cascaded support vector machines

Keiji Shimada, Tetsu Matsukawa, Yoshihiro Noguchi, Takio Kurita

研究成果: Chapter in Book/Report/Conference proceedingConference contribution

9 引用 (Scopus)

抜粋

Facial expression recognition is one of the most challenging research area in the image recognition field and has been studied actively for a long time. Especially, we think that smile is important facial expression to communicate well between human beings and also between human and machines. Therefore, if we can detect smile and also estimate its intensity at low calculation cost and high accuracy, it will raise the possibility of inviting many new applications in the future. In this paper, we focus on smile in facial expressions and study feature extraction methods to detect a smile and estimate its intensity only by facial appearance information (Facial parts detection, not required). We use Local Intensity Histogram (LIH), Center-Symmetric Local Binary Pattern (CS-LBP) or features concatenated LIH and CS-LBP to train Support Vector Machine (SVM) for smile detection. Moreover, we construct SVM smile detector as a cascaded structure both to keep the performance and reduce the calculation cost, and estimate the smile intensity by posterior probability. As a consequence, we achieved both low calculation cost and high performance with practical images and we also implemented the proposed methods to the PC demonstration system.

元の言語英語
ホスト出版物のタイトルComputer Vision - ACCV 2010 Workshops - ACCV 2010 International Workshops, Revised Selected Papers
ページ277-286
ページ数10
エディションPART1
DOI
出版物ステータス出版済み - 9 28 2011
外部発表Yes
イベントInternational Workshops on Computer Vision, ACCV 2010 - Queenstown, ニュージ―ランド
継続期間: 11 8 201011 9 2010

出版物シリーズ

名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
番号PART1
6468 LNCS
ISSN(印刷物)0302-9743
ISSN(電子版)1611-3349

その他

その他International Workshops on Computer Vision, ACCV 2010
ニュージ―ランド
Queenstown
期間11/8/1011/9/10

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

フィンガープリント Appearance-based smile intensity estimation by cascaded support vector machines' の研究トピックを掘り下げます。これらはともに一意のフィンガープリントを構成します。

  • これを引用

    Shimada, K., Matsukawa, T., Noguchi, Y., & Kurita, T. (2011). Appearance-based smile intensity estimation by cascaded support vector machines. : Computer Vision - ACCV 2010 Workshops - ACCV 2010 International Workshops, Revised Selected Papers (PART1 版, pp. 277-286). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); 巻数 6468 LNCS, 番号 PART1). https://doi.org/10.1007/978-3-642-22822-3_28