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
Country/TerritoryJapan
CityTsukuba Science City
Period05/5/1605/5/18

ASJC Scopus subject areas

  • Computer Vision and Pattern Recognition

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