Tracking articulated hand motion with eigen dynamics analysis

Hanning Zhou, Thomas S. Huang

Research output: Contribution to conferencePaperpeer-review

Abstract

This paper introduces the concept ofeigen-dynamics and proposes an eigen dynamics analysis (EDA) method to learn the dynamics of natural hand motion from labelled sets of motion captured with a data glove. The result is parameterized with a high-order stochastic linear dynamic system (LDS) consisting of five lower-order LDS. Each corresponding to one eigen-dynamics. Based on the EDA model, we construct a dynamic Bayesian network (DBN) to analyze the generative process of a image sequence of natural hand motion. Using the DBN, a hand tracking system is implemented. Experiments on both synthesized and real-world data demonstrate the robustness and effectiveness of these techniques.

Original languageEnglish (US)
Pages1102-1109
Number of pages8
StatePublished - 2003
EventNINTH IEEE INTERNATIONAL CONFERENCE ON COMPUTER VISION - Nice, France
Duration: Oct 13 2003Oct 16 2003

Other

OtherNINTH IEEE INTERNATIONAL CONFERENCE ON COMPUTER VISION
CountryFrance
CityNice
Period10/13/0310/16/03

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition

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