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Contrôle d'un système multi-CNN via le cap magnétique du smartphone pour la reconnaissance de scènes indoor

Andrea Daou 1, 2, 3 Jean-Baptiste Pothin 1 Paul Honeine 2 Abdelaziz Bensrhair 3 
2 App - LITIS - Equipe Apprentissage
LITIS - Laboratoire d'Informatique, du Traitement de l'Information et des Systèmes
3 STI - LITIS - Equipe Systèmes de Transport Intelligent
LITIS - Laboratoire d'Informatique, du Traitement de l'Information et des Systèmes
Abstract : In computer vision, indoor scene recognition consists of identifying a particular room from an image. The major difficulty is the high complexity of indoor environments compared to outdoor ones. This paper proposes an indoor scene classification system based on built-in smartphones sensors. The proposed method investigates both visual information and smartphone’s magnetic heading. The presented system consists of direction-driven multi-CNNs, each one specific for a definite range of orientations and assisted by the smartphone’s camera magnetic heading. The user is room-level localized while simply capturing an image with a smartphone. The performance of the system is validated by experiments on a real dataset.
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https://hal-normandie-univ.archives-ouvertes.fr/hal-03749199
Contributor : Paul Honeine Connect in order to contact the contributor
Submitted on : Wednesday, August 10, 2022 - 3:13:32 PM
Last modification on : Friday, August 12, 2022 - 3:32:13 AM
Long-term archiving on: : Friday, November 11, 2022 - 6:52:23 PM

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  • HAL Id : hal-03749199, version 1

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Andrea Daou, Jean-Baptiste Pothin, Paul Honeine, Abdelaziz Bensrhair. Contrôle d'un système multi-CNN via le cap magnétique du smartphone pour la reconnaissance de scènes indoor. 28-ème Colloque GRETSI sur le Traitement du Signal et des Images, Sep 2022, Nancy, France. ⟨hal-03749199⟩

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