Dynamic data driven coupling of continuous and discrete methods for 3D tracking

Dimitris Metaxas, Gabriel Tsechpenakis

Research output: Contribution to journalConference articlepeer-review

3 Scopus citations


We present a new framework for robust 3D tracking, using a dynamic data driven coupling of continuous and discrete methods to overcome their limitations. Our method uses primarily the continuous-based tracking which is replaced by the discrete one, to obtain model re-initializations when necessary. We use the error in the continuous tracking to learn off-line, based on SVMs, when the continuous-based tracking fails and switch between the two methods. We develop a novel discrete method for 3D shape configuration estimation, which utilizes both frame and multi-frame features, taking into account the most recent input frames, using a time-window. We therefore overcome the error accumulation over time, that most continuous methods suffer from and simultaneously reduce the discrete methods complexity and prevent possible multiple solutions in shape estimation. We demonstrate the power of our framework in complex hand tracking sequences with large rotations, articulations, lighting changes and occlusions.

Original languageEnglish (US)
Pages (from-to)712-720
Number of pages9
JournalLecture Notes in Computer Science
Issue numberII
StatePublished - 2005
Event5th International Conference on Computational Science - ICCS 2005 - Atlanta, GA, United States
Duration: May 22 2005May 25 2005

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • General Computer Science


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