Gaze Estimation Using Regression Analysis and AAMs Parameters Selected Based on Information Criterion

  • Manabu Takatani
  • Yasuo Ariki
  • Tetsuya Takiguchi
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6468)


One of the most crucial techniques associated with Computer Vision is technology that deals with the automatic estimation of gaze orientation. In this paper, a method is proposed to estimate horizontal gaze orientation from a monocular camera image using the parameters of Active Appearance Models (AAM) selected based on several model selection methods. The proposed method can estimate horizontal gaze orientation more precisely than the conventional method (Ishikawa’s method) because of the following two unique points: simultaneous estimation of horizontal head pose and gaze orientation, and the most suitable model formula for regression selected based on each model selection method. The validity of the proposed method was confirmed by experimental results.


Akaike Information Criterion Feature Point Parameter Vector Training Image Minimum Description Length 
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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Manabu Takatani
    • 1
  • Yasuo Ariki
    • 2
  • Tetsuya Takiguchi
    • 2
  1. 1.Graduate School of EngineeringKobe UniversityJapan
  2. 2.Organization of Advanced Science and TechnologyKobe UniversityJapan

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