Abstract
This paper presents a 3D Vision-Based Shelf Monitoring system (3D-VSM) aimed at automatically estimating the On-Shelf Availability (OSA) of products in a retail store. The proposed solution exploits 3D data returned by a consumer-grade depth sensor to provide up-to-date information about product availability for customer purchase and eventually generate alerts on Out-Of-Stock (OOS) events, based on the comparison between a reference model of the shelf and its current status. The main advantage is that no a priori knowledge about the product characteristics is required, while the shelf reference model is automatically built, based on an initial training stage. The 3D-VSM system is integrated into an e-commerce application for electronic shopping and home delivery, developed in the context of the E-SHELF research project. Experimental tests carried out in a retail store show that the system is able to accurately estimate the on-shelf availability of products, overcoming time and labour problems of conventional audits.
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Acknowledgements
The financial support of the grant Electronic Shopping & Home delivery of Edible goods with Low environmental Footprint (E-SHELF), POR Puglia FESR-FSE 2014–2020 (Grant Id. OSW3NO1) is gratefully acknowledged. The authors are thankful to Primo Prezzo (Carelli) for providing test facilities and valuable support in performing the experiments. The administrative and technical support by Vito Micunco (Software Design), Michele Attolico (CNR-STIIMA) and Giuseppe Bono (CNR-STIIMA) is also gratefully acknowledged.
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Milella, A., Marani, R., Petitti, A., Cicirelli, G., D’Orazio, T. (2021). 3D Vision-Based Shelf Monitoring System for Intelligent Retail. In: Del Bimbo, A., et al. Pattern Recognition. ICPR International Workshops and Challenges. ICPR 2021. Lecture Notes in Computer Science(), vol 12662. Springer, Cham. https://doi.org/10.1007/978-3-030-68790-8_35
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