Tracking 3d pose of rigid object by sparse template matching

Yuki Oka, Toshiyuki Kuroda, Tsuyoshi Migita, Takeshi Shakunaga

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

5 Citations (Scopus)

Abstract

Tracking 3d pose of a known object is one of the most important problems in computer vision. This paper proposes an appearance-based approach to this problem by combining the sparse template matching and the particle filter. Although the combination of them has already been discussed for 2d tracker, it has not been applied for efficient 3d tracking. This paper discusses an appearance-based tracker when a surface model of the target 3d object and the initial pose are given. The fundamental framework of the particle filter is provided at first for implementing a pose tracker based on sparse 3d template matching. Then, the coarse-to-fine approach is introduced for efficient implementation. Although the fundamental particle filter often requires a lot of particles for sufficient tracking, the number of particles can be effectively reduced by the coarse-to-fine strategy. Experimental results for both the simulation data and real images show how the proposed method works in frame rate on 3GHz Core 2 Quad(single thread) without using GPU or other special hardware.

Original languageEnglish
Title of host publicationProceedings of the 5th International Conference on Image and Graphics, ICIG 2009
PublisherIEEE Computer Society
Pages390-397
Number of pages8
ISBN (Print)9780769538839
DOIs
Publication statusPublished - Jan 1 2009
Event5th International Conference on Image and Graphics, ICIG 2009 - Xi'an, Shanxi, China
Duration: Sep 20 2009Sep 23 2009

Publication series

NameProceedings of the 5th International Conference on Image and Graphics, ICIG 2009

Other

Other5th International Conference on Image and Graphics, ICIG 2009
CountryChina
CityXi'an, Shanxi
Period9/20/099/23/09

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design
  • Computer Vision and Pattern Recognition

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