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Physiological modelling for improved reliability in silhouette-driven gradient-based hand tracking | IEEE Conference Publication | IEEE Xplore
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Physiological modelling for improved reliability in silhouette-driven gradient-based hand tracking


Abstract:

We present a gradient-based motion capture system that robustly tracks a human hand, based on abstracted visual information - silhouettes. Despite the ambiguity in the vi...Show More

Abstract:

We present a gradient-based motion capture system that robustly tracks a human hand, based on abstracted visual information - silhouettes. Despite the ambiguity in the visual data and despite the vulnerability of gradient-based methods in the face of such ambiguity, we minimise problems related to misfit by using a model of the hand's physiology, which is entirely non-visual, subject-invariant, and assumed to be known a priori. By modelling seven distinct aspects of the hand's physiology we derive prior densities which are incorporated into the tracking system within a Bayesian framework. We demonstrate how the posterior is formed, and how our formulation leads to the extraction of the maximum a posteriori estimate using a gradient-based search. Our results demonstrate an enormous improvement in tracking precision and reliability, while also achieving near real-time performance.
Date of Conference: 20-25 June 2009
Date Added to IEEE Xplore: 18 August 2009
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ISSN Information:

Conference Location: Miami, FL, USA

References

References is not available for this document.