Hybrid One-Shot 3D Hand Pose Estimation by Exploiting Uncertainties

Georg Poier, Konstantinos Roditakis, Samuel Schulter, Damien Michel, Horst Bischof and Antonis A. Argyros

Abstract

Model-based approaches to 3D hand tracking have been shown to perform well in a wide range of scenarios. However, they require initialisation and cannot recover easily from tracking failures that occur due to fast hand motions. Data-driven approaches, on the other hand, can quickly deliver a solution, but the results often suffer from lower accuracy or missing anatomical validity compared to those obtained from model-based approaches. In this work we propose a hybrid approach for hand pose estimation from a single depth image. First, a learned regressor is employed to deliver multiple initial hypotheses for the 3D position of each hand joint. Subsequently, the kinematic parameters of a 3D hand model are found by deliberately exploiting the inherent uncertainty of the inferred joint proposals. This way, the method provides anatomically valid and accurate solutions without requiring manual initialisation or suffering from track losses. Quantitative results on several standard datasets demonstrate that the proposed method outperforms state-of-the-art representatives of the model-based, data-driven and hybrid paradigms.

Session

Tracking and Pose Estimation

Files

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DOI

10.5244/C.29.182
https://dx.doi.org/10.5244/C.29.182

Citation

Georg Poier, Konstantinos Roditakis, Samuel Schulter, Damien Michel, Horst Bischof and Antonis A. Argyros. Hybrid One-Shot 3D Hand Pose Estimation by Exploiting Uncertainties. In Xianghua Xie, Mark W. Jones, and Gary K. L. Tam, editors, Proceedings of the British Machine Vision Conference (BMVC), pages 182.1-182.14. BMVA Press, September 2015.

Bibtex

@inproceedings{BMVC2015_182,
	title={Hybrid One-Shot 3D Hand Pose Estimation by Exploiting Uncertainties},
	author={Georg Poier and Konstantinos Roditakis and Samuel Schulter and Damien Michel and Horst Bischof and Antonis A. Argyros},
	year={2015},
	month={September},
	pages={182.1-182.14},
	articleno={182},
	numpages={14},
	booktitle={Proceedings of the British Machine Vision Conference (BMVC)},
	publisher={BMVA Press},
	editor={Xianghua Xie, Mark W. Jones, and Gary K. L. Tam},
	doi={10.5244/C.29.182},
	isbn={1-901725-53-7},
	url={https://dx.doi.org/10.5244/C.29.182}
}