Head pose estimation system based on particle filtering with adaptive diffusion control

Kenji Oka, Yoichi Sato, Yasuto Nakanishi, Hideki Koike

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

25 Citations (Scopus)

Abstract

In this paper, we propose a new tracking system based on a stochastic filtering framework for reliably estimating the 3D pose of a user's head in real-time. Our system estimates the pose of a user.s head in each image frame whose 3D model is automatically obtained at an initialization step. In particular, our estimation method is designed to control the diffusion factor of a motion model adaptively. This technique contributes significantly to improving the following performance simultaneously: the robust tracking against abrupt head motion and the accurate pose estimation when the user is staring at a point in a scene. The performance of our proposed method has been successfully demonstrated via experiments.

Original languageEnglish
Title of host publicationProceedings of the 9th IAPR Conference on Machine Vision Applications, MVA 2005
Pages586-589
Number of pages4
Publication statusPublished - 2005 Dec 1
Externally publishedYes
Event9th IAPR Conference on Machine Vision Applications, MVA 2005 - Tsukuba Science City, Japan
Duration: 2005 May 162005 May 18

Publication series

NameProceedings of the 9th IAPR Conference on Machine Vision Applications, MVA 2005

Other

Other9th IAPR Conference on Machine Vision Applications, MVA 2005
CountryJapan
CityTsukuba Science City
Period05/5/1605/5/18

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

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  • Cite this

    Oka, K., Sato, Y., Nakanishi, Y., & Koike, H. (2005). Head pose estimation system based on particle filtering with adaptive diffusion control. In Proceedings of the 9th IAPR Conference on Machine Vision Applications, MVA 2005 (pp. 586-589). (Proceedings of the 9th IAPR Conference on Machine Vision Applications, MVA 2005).