BIM: Ball intersection multi template matching

Bat El Shlomo, Shai Avidan

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

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.

Original languageEnglish
Title of host publicationBritish Machine Vision Conference 2017, BMVC 2017
PublisherBMVA Press
ISBN (Electronic)190172560X, 9781901725605
StatePublished - 2017
Event28th British Machine Vision Conference, BMVC 2017 - London, United Kingdom
Duration: 4 Sep 20177 Sep 2017

Publication series

NameBritish Machine Vision Conference 2017, BMVC 2017

Conference

Conference28th British Machine Vision Conference, BMVC 2017
Country/TerritoryUnited Kingdom
CityLondon
Period4/09/177/09/17

Funding

FundersFunder number
Israel Science Foundation1917/2015
Israel Science Foundation

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