Hundreds of millions of images are uploaded to the cloud every day. Innovative applications able to analyze and extract efficiently information from such a big database are needed nowadays more than ever. Visual search is an application able to retrieve information of a query image comparing it against a large image database. In this paper a Visual Search pipeline implementation is presented able to retrieve multiple objects depicted in a single query image. Quantitative and qualitative precision results are shown on both real and synthetic datasets.

Visual Search of multiple objects from a single query

PARACCHINI, MARCO BRANDO MARIO;MARCON, MARCO;
2016-01-01

Abstract

Hundreds of millions of images are uploaded to the cloud every day. Innovative applications able to analyze and extract efficiently information from such a big database are needed nowadays more than ever. Visual search is an application able to retrieve information of a query image comparing it against a large image database. In this paper a Visual Search pipeline implementation is presented able to retrieve multiple objects depicted in a single query image. Quantitative and qualitative precision results are shown on both real and synthetic datasets.
2016
Proceedings of the 6th International Conference on Consumer Electronics - Berlin (ICCE-Berlin), 2016 IEEE
978-1-5090-2096-6
Visual Search, Retrieval, multi-objects retrieval, Pairwise-matching, SIFT
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/999854
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