On Partial Least Squares in Head Pose Estimation: How to simultaneously deal with misalignment

Murad Al Haj*, Jordi Gonzalez, Larry S. Davis

*Corresponding author for this work

Research output: Contribution to journalArticleResearchpeer-review

84 Citations (Scopus)

Abstract

Head pose estimation is a critical problem in many computer vision applications. These include human computer interaction, video surveillance, face and expression recognition. In most prior work on heads pose estimation, the positions of the faces on which the pose is to be estimated are specified manually. Therefore, the results are reported without studying the effect of misalignment. We propose a method based on partial least squares (PLS) regression to estimate pose and solve the alignment problem simultaneously. The contributions of this paper are two-fold: 1) we show that the kernel version of PLS (kPLS) achieves better than state-of-the-art results on the estimation problem and 2) we develop a technique to reduce misalignment based on the learned PLS factors.

Original languageEnglish
Pages (from-to)2602-2609
Number of pages8
JournalIEEE Conference on Computer Vision and Pattern Recognition
Volume(GGS Rating A++, Class 1)
Publication statusPublished - 2012

Keywords

  • RECOGNITION
  • POINT

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