Hardware-assisted multiple object tracking for human-robot-interaction

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Hardware-assisted multiple object tracking for human-robot-interaction

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ACM/IEEE International Conference on Human-Robot Interaction archive
Proceedings of the 4th ACM/IEEE international conference on Human robot interaction table of contents

La Jolla, California, USA

SESSION: HRI late-breaking abstracts table of contents

Pages 283-284

Year of Publication: 2009

ISBN:978-1-60558-404-1

Authors

Claus Lenz	Technische Universität München, München, Germany
Giorgio Panin	Technische Universität München, München, Germany
Thorsten Röder	Technische Universität München, München, Germany
Martin Wojtczyk	Technische Universität München, München, Germany
Alois Knoll	Technische Universität München, München, Germany

Sponsors

SIGART: ACM Special Interest Group on Artificial Intelligence
SIGCHI: ACM Special Interest Group on Computer-Human Interaction
ACM: Association for Computing Machinery

Publisher

ACM New York, NY, USA

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REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

	1	Michael Isard , Andrew Blake, C $ONDENSATION$ —Conditional Density Propagation forVisual Tracking, International Journal of Computer Vision, v.29 n.1, p.5-28, Aug. 1998 [doi>10.1023/A:1008078328650]
	2	C. Lenz, S. Nair, A. Knoll, W. Rösel, J. Gast, F. Wallhoff, and M. Rickert. Joint-action for humans and industrial robots for assembly tasks. In RO-MAN 08: Proceedings of the 17th IEEE International Symposium on Robot and Human Interactive Communication, München, Germany, 2008. IEEE Robotic and Automation Society.
	3	C. Lenz, G. Panin, and A. Knoll. A GPU-accelerated particle filter with pixel-level likelihood. In International Workshop on Vision, Modeling and Visualization (VMV), Konstanz, Germany, Oct. 2008.
	4	Julie L. Marble , David J. Bruemmer , Douglas A. Few , Donald D. Dudenhoeffer, Evaluation of Supervisory vs. Peer-Peer Interaction with Human-Robot Teams, Proceedings of the Proceedings of the 37th Annual Hawaii International Conference on System Sciences (HICSS'04) - Track 5, p.50130.2, January 05-08, 2004
	5	M. Yang and N. Ahuja. Gaussian Mixture Model for Human Skin Color and Its Application in Image and Video Databases. In Proc. SPIE: Storage and Retrieval for Image and Video Databases VII, volume 3656, pages 458--466, 1999.