@inproceedings{5e8735a1cbbf4d9e909012e898f1160b,
title = "BIM: Ball intersection multi template matching",
abstract = "BIM is a multi-template matching algorithm. As opposed to traditional template matching algorithms that match a single template to a single image, BIM attempts to match multiple templates to a single image at once. A naive approach to multi-template matching would be to run a standard template matching algorithm sequentially with each of the templates and report the best result. Instead, each template processed by BIM further restricts the search space of the following templates, thus speeding up the overall process. In particular, we extend a recently introduced method for single template matching under 2D affine transformation to work with multiple templates at once. As a result, given a library of templates we can efficiently find the best 2D affine transformation for each of them in a target image. Experiments on real data sets reveal speedups of between 10 and 17.",
author = "{El Shlomo}, Bat and Shai Avidan",
note = "Publisher Copyright: {\textcopyright} 2017. The copyright of this document resides with its authors.; 28th British Machine Vision Conference, BMVC 2017 ; Conference date: 04-09-2017 Through 07-09-2017",
year = "2017",
language = "الإنجليزيّة",
series = "British Machine Vision Conference 2017, BMVC 2017",
booktitle = "British Machine Vision Conference 2017, BMVC 2017",
}