Head Pose Estimation Using Multi-scale Gaussian Derivatives

  • Varun Jain
  • James L. Crowley
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7944)

Abstract

In this paper we approach the problem of head pose estimation by combining Multi-scale Gaussian Derivatives with Support Vector Machines.

We evaluate the approach on the Pointing04 and CMU-PIE data sets and to estimate the pan and tilt of the head from facial images. We achieved a mean absolute error of 6.9 degrees for pan and 8.0 degrees for tilt on the Pointing04 data set.

Keywords

Support Vector Machine Gesture Recognition Automatic Face Radial Basis Kernel Deictic Gesture 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Varun Jain
    • 1
    • 2
  • James L. Crowley
    • 1
    • 3
  1. 1.INRIA Grenoble Rhône-AlpesFrance
  2. 2.Université de GrenobleFrance
  3. 3.Grenoble INPFrance

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