CUED Publications database

Physiological modelling for improved reliability in silhouette-driven gradient-based hand tracking

Kaimakis, P and Lasenby, J (2009) Physiological modelling for improved reliability in silhouette-driven gradient-based hand tracking. 2009 IEEE Conference on Computer Vision and Pattern Recognition, CVPR 2009. pp. 19-26.

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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. © 2009 IEEE.

Item Type: Article
Subjects: UNSPECIFIED
Divisions: Div F > Signal Processing and Communications
Depositing User: Cron Job
Date Deposited: 07 Mar 2014 12:19
Last Modified: 27 Nov 2014 19:20
DOI: 10.1109/CVPR.2009.5204252