Towards a Robust Solution for the Supermarket Shelf Audit Problem

Emmanuel Morán; Boris Vintimilla; Miguel Realpe

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Paper

Towards a Robust Solution for the Supermarket Shelf Audit Problem

Topics: Assistive Computer Vision; Object Detection and Localization; Simultaneous Localization and Mapping; Transfer Learning; Vision for Robotics

In Proceedings of the 18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications - Volume 4 VISAPP: VISAPP, 912-919, 2023 , Lisbon, Portugal

Authors: Emmanuel Morán ; Boris Vintimilla and Miguel Realpe

Affiliation: ESPOL Polytechnic University, Escuela Superior Politecnica del Litoral, ESPOL, CIDIS, Campus Gustavo Galindo Km. 30.5 Vía Perimetral, P.O. Box 09-01-5863, Guayaquil, Ecuador

Keyword(s): Retail, Supermarket, Shelves Auditing, Deep Learning, Supermarket Dataset.

Abstract: Retail supermarket is an industrial sector with repetitive tasks performed using visual analysis by the store’s operators. Tasks such as checking the status of the shelves can contain multiple sequential sub-tasks, each of which needs to be performed correctly. In recent years, there has been some intents to create a solution for the tasks mentioned without been complete solution for retails. In this article, a first realistic approach is proposed to solve the supermarket shelf audit problem. For this, a workflow is presented to deliver compliance level with respect to the expected store’s planogram.

CC BY-NC-ND 4.0

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Paper citation in several formats:

Morán, E.; Vintimilla, B. and Realpe, M. (2023). Towards a Robust Solution for the Supermarket Shelf Audit Problem. In Proceedings of the 18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2023) - Volume 4: VISAPP; ISBN 978-989-758-634-7; ISSN 2184-4321, SciTePress, pages 912-919. DOI: 10.5220/0011747000003417

@conference{visapp23,
author={Emmanuel Morán. and Boris Vintimilla. and Miguel Realpe.},
title={Towards a Robust Solution for the Supermarket Shelf Audit Problem},
booktitle={Proceedings of the 18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2023) - Volume 4: VISAPP},
year={2023},
pages={912-919},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011747000003417},
isbn={978-989-758-634-7},
issn={2184-4321},
}

TY - CONF

JO - Proceedings of the 18th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Applications (VISIGRAPP 2023) - Volume 4: VISAPP
TI - Towards a Robust Solution for the Supermarket Shelf Audit Problem
SN - 978-989-758-634-7
IS - 2184-4321
AU - Morán, E.
AU - Vintimilla, B.
AU - Realpe, M.
PY - 2023
SP - 912
EP - 919
DO - 10.5220/0011747000003417
PB - SciTePress