Towards a Robust Solution for the Supermarket Shelf Audit Problem: Obsolete Price Tags in Shelves

Emmanuel F. Morán, Boris Xavier Vintimilla, Miguel Realpe

Abstract: Shelf auditing holds significant importance within the retail industry’s industrial sector. It encompasses various processes carried out by human operators. This article aims to address the issue of identifying outdated price tags on shelves, bridging the gap of an automated shelf audit. Our proposal introduces a minimum viable process that effectively detects, recognizes, and locates price tags using computer vision and deep learning techniques. The outcomes of this study demonstrate the robustness of our approach in generating a comprehensive list of price tags on shelves, which can be subsequently compared with a database to identify and flag obsolete ones.

External IDs:dblp:conf/ciarp/MoranVR23