@conference {cPont-Tuset12a,
	title = {Upper-bound assessment of the spatial accuracy of hierarchical region-based image representations},
	booktitle = {IEEE International Conference on Acoustics, Speech, and Signal Processing},
	year = {2012},
	month = {03/2012},
	pages = {865-868},
	abstract = {<p>Hierarchical region-based image representations are versatile tools for segmentation, filtering, object detection, etc.\&nbsp;The evaluation of their spatial accuracy has been usually performed assessing the final result of an algorithm based on\&nbsp;this representation.\&nbsp;Given its wide applicability, however, a direct supervised assessment, independent of any application, would be desirable and fair.</p><p>A brute-force assessment of all the partitions represented in the hierarchical structure would be a correct approach,\&nbsp;but as we prove formally, it is computationally unfeasible.\&nbsp;This paper presents an efficient algorithm to find the upper-bound performance of the representation and we show\&nbsp;that the previous approximations in the literature can fail at finding this bound.</p>},
	isbn = {978-1-4673-0044-5},
	doi = {10.1109/ICASSP.2012.6288021},
	author = {Jordi Pont-Tuset and Marqu{\'e}s, F.}
}
