Boosting the Performance of Model-based 3D Tracking by Employing Low Level Motion Cues

Ammar Qammaz, Nikolaos Kyriazis and Antonis A. Argyros

Abstract

3D tracking of objects and hands in an object manipulation scenario is a very interesting computer vision problem with a wide variety of applications ranging from consumer electronics to robotics and medicine. Recent advances in this research topic allow for 3D tracking of complex scenarios involving bi-manual manipulation of several rigid objects using commodity hardware and with high accuracy. The problem with these approaches is that their computational complexity is proportional to the number of objects in the scene. The problem with these approaches is that they treat tracking as a search problem whose dimensionality increases with the number of objects in the scene. In this paper we present a method that utilizes simple low level motion cues for dynamically assigning computational resources to parts of the scene where they are actually required. In a series of experiments, we show that this simple idea improves tracking performance dramatically at a cost of only a minor degradation of tracking accuracy.

Session

Poster 2

Files

Extended Abstract (PDF, 2M)
Paper (PDF, 4M)
Supplemental Materials (ZIP, 15M)

DOI

10.5244/C.29.144
https://dx.doi.org/10.5244/C.29.144

Citation

Bibtex

@inproceedings{BMVC2015_144,
	title={Boosting the Performance of Model-based 3D Tracking by Employing Low Level Motion Cues},
	author={Ammar Qammaz and Nikolaos Kyriazis and Antonis A. Argyros},
	year={2015},
	month={September},
	pages={144.1-144.11},
	articleno={144},
	numpages={11},
	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.29.144},
	isbn={1-901725-53-7},
	url={https://dx.doi.org/10.5244/C.29.144}
}