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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 alldoi:10.1145/1991996.1992016 dblp:conf/mir/KalantidisPTZA11 fatcat:fvghbgtzczaavasxefrbhna2qe