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The Estimation of Hand Pose Based on Mean-Shift Tracking Using the Fusion of Color and Depth Information for Marker-less Augmented Reality

  • Journal of The Korea Society of Computer and Information
  • Abbr : JKSCI
  • 2012, 17(7), pp.155-166
  • Publisher : The Korean Society Of Computer And Information
  • Research Area : Engineering > Computer Science

이선형 1 Hernsoo Hahn 1 Youngjun Han 1

1숭실대학교

Accredited

ABSTRACT

This paper proposes a new method of estimating the hand pose through the Mean-Shift tracking algorithm using the fusion of color and depth information for marker-less augmented reality. On marker-less augmented reality, the most of previous studies detect the hand region using the skin color from simple experimental background. Because finger features should be detected on the hand, the hand pose that can be measured from cameras is restricted considerably. However, the proposed method can easily detect the hand pose from complex background through the new Mean-Shift tracking method using the fusion of the color and depth information from 3D sensor. The proposed method of estimating the hand pose uses the gravity point and two random points on the hand without largely constraints. The proposed Mean-Shift tracking method has about 50 pixels error less than general tracking method just using color value. The augmented reality experiment of the proposed method shows results of its performance being as good as marker based one on the complex background.

Citation status

* References for papers published after 2023 are currently being built.

This paper was written with support from the National Research Foundation of Korea.