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Painting recognition from wearable cameras

Théophile Dalens 1, * Josef Sivic 1 Ivan Laptev 1 Marine Campedel 2 
* Corresponding author
1 WILLOW - Models of visual object recognition and scene understanding
DI-ENS - Département d'informatique - ENS Paris, Inria Paris-Rocquencourt, CNRS - Centre National de la Recherche Scientifique : UMR8548
2 Télécom ParisTech - TSI
LTCI - Laboratoire Traitement et Communication de l'Information
Abstract : Are smart glasses the new high-tech device that will guide you through a museum? In this report, we describe a system that runs "on device" on Google Glass and retrieves the painting you're looking at among a set of paintings in a database. We perform an experimental comparison of the accuracy and speed of different feature detectors and descriptors on a realistic dataset of paintings from Musée du Louvre. Based on this analysis we design an algorithm for fast and accurate image matching using bags of binary features. We develop an application that runs directly on Google Glass without sending images to external servers for processing and recognizes a query painting in a database of 100 paintings in one second. The code is available online.
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Submitted on : Tuesday, September 9, 2014 - 11:27:35 AM
Last modification on : Thursday, March 17, 2022 - 10:08:39 AM
Long-term archiving on: : Wednesday, December 10, 2014 - 11:40:56 AM


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  • HAL Id : hal-01062126, version 1


Théophile Dalens, Josef Sivic, Ivan Laptev, Marine Campedel. Painting recognition from wearable cameras. [Contract] 2014, pp.13. ⟨hal-01062126⟩



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