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Head Pose Estimation on Low Resolution Images

  • Nicolas Gourier
  • Jérôme Maisonnasse
  • Daniela Hall
  • James L. Crowley
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4122)

Abstract

This paper addresses the problem of estimating head pose over a wide range of angles from low-resolution images. Faces are detected using chrominance-based features. Grey-level normalized face imagettes serve as input for linear auto-associative memory. One memory is computed for each pose using a Widrow-Hoff learning rule. Head pose is classified with a winner-takes-all process. We compare results from our method with abilities of human subjects to estimate head pose from the same data set. Our method achieves similar results in estimating orientation in tilt (head nodding) angle, and higher precision for estimating orientation in the pan (side-to-side) angle.

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Copyright information

© Springer Berlin Heidelberg 2007

Authors and Affiliations

  • Nicolas Gourier
    • 1
  • Jérôme Maisonnasse
    • 1
  • Daniela Hall
    • 1
  • James L. Crowley
    • 1
  1. 1.PRIMA, GRAVIR-IMAG, INRIA Rhône-Alpes, 38349 St. IsmierFrance

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