Scalable triangulation-based logo recognition

DSpace/Manakin Repository

Show simple item record

dc.contributor.author Kalantidis, Y en
dc.contributor.author Pueyo, LG en
dc.contributor.author Trevisiol, M en
dc.contributor.author Van Zwol, R en
dc.contributor.author Avrithis, Y en
dc.date.accessioned 2014-03-01T02:53:27Z
dc.date.available 2014-03-01T02:53:27Z
dc.date.issued 2011 en
dc.identifier.uri https://dspace.lib.ntua.gr/xmlui/handle/123456789/36330
dc.subject.other Bag of words en
dc.subject.other Class models en
dc.subject.other Data sets en
dc.subject.other Delaunay triangulation en
dc.subject.other Indexing process en
dc.subject.other Inverted index structures en
dc.subject.other Local geometry en
dc.subject.other Logo recognition en
dc.subject.other Multiscales en
dc.subject.other Query images en
dc.subject.other Search problem en
dc.subject.other Triangulation-based en
dc.subject.other Visual appearance en
dc.subject.other Data processing en
dc.subject.other Visualization en
dc.subject.other Triangulation en
dc.title Scalable triangulation-based logo recognition en
heal.type conferenceItem en
heal.identifier.primary 10.1145/1991996.1992016 en
heal.identifier.secondary http://dx.doi.org/10.1145/1991996.1992016 en
heal.publicationDate 2011 en
heal.abstract We propose a scalable logo recognition approach that extends the common bag-of-words model and incorporates local geometry in the indexing process. Given a query image and a large logo database, the goal is to recognize the logo contained in the query, if any. We locally group features in triples using multi-scale Delaunay triangulation and represent triangles by signatures capturing both visual appearance and local geometry. Each class is represented by the union of such signatures over all instances in the class. We see large scale recognition as a sub-linear search problem where signatures of the query image are looked up in an inverted index structure of the class models. We evaluate our approach on a large-scale logo recognition dataset with more than four thousand classes. © 2011 ACM. en
heal.journalName Proceedings of the 1st ACM International Conference on Multimedia Retrieval, ICMR'11 en
dc.identifier.doi 10.1145/1991996.1992016 en

Files in this item

Files Size Format View

There are no files associated with this item.

This item appears in the following Collection(s)

Show simple item record