Query driven localized linear discriminant models for head pose estimation

Zhu Li*, Yun Fu, Junsong Yuan, Thomas S. Huang, Ying Wu

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

31 Scopus citations

Abstract

Head pose appearances under the pan and tilt variations span a high dimensional manifold that has complex structures and local variations. For pose estimation purpose, we need to discover the subspace structure of the manifold and learn discriminative subspaces/metrics for head pose recognition. The performance of the head pose estimation is heavily dependent on the accuracy of structure learnt and the discriminating power of the metric. In this work we develop a query point driven, localized linear subspace learning method that approximates the non-linearity of the head pose manifold structure with piece-wise linear discriminating subspaces/metrics. Simulation results demonstrate the effectiveness of the proposed solution in both accuracy and computational efficiency.

Original languageEnglish (US)
Title of host publicationProceedings of the 2007 IEEE International Conference on Multimedia and Expo, ICME 2007
Pages1810-1813
Number of pages4
StatePublished - Dec 1 2007
EventIEEE International Conference onMultimedia and Expo, ICME 2007 - Beijing, China
Duration: Jul 2 2007Jul 5 2007

Publication series

NameProceedings of the 2007 IEEE International Conference on Multimedia and Expo, ICME 2007

Other

OtherIEEE International Conference onMultimedia and Expo, ICME 2007
CountryChina
CityBeijing
Period7/2/077/5/07

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design
  • Software

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    Li, Z., Fu, Y., Yuan, J., Huang, T. S., & Wu, Y. (2007). Query driven localized linear discriminant models for head pose estimation. In Proceedings of the 2007 IEEE International Conference on Multimedia and Expo, ICME 2007 (pp. 1810-1813). [4285024] (Proceedings of the 2007 IEEE International Conference on Multimedia and Expo, ICME 2007).