Technical University of Munich

@inproceedings{hanek_fast_2002,
 author = {R Hanek and T Schmitt and S Buck and M Beetz},
 title = {Fast Image-based Object Localization in Natural Scenes},
 booktitle = {{IEEE/RSJ} International Conference on Intelligent Robots and Systems
	({IROS)} 2002},
 year = {2002},
 series = {Lausanne},
 pages = {116–122},
 abstract = {In many robot applications, autonomous robots must be capable of localizing
	the objects they are to manipulate. In this paper we address the
	object localization problem by fitting a parametric curve model to
	the object contour in the image. The initial prior of the object
	pose is iteratively refined to the posterior distribution by optimizing
	the separation of the object and the background. The local separation
	criteria are based on local statistics which are iteratively computed
	from the object and the background region. No prior knowledge on
	color distributions is needed. Experiments show that the method is
	capable of localizing objects in a cluttered and textured scene even
	under strong variations of illumination. The method is able to localize
	a soccer ball within frame rate.},
}