Product recognition in store shelves as a sub-graph isomorphism problem
Abstract
The arrangement of products in store shelves is carefully planned to maximize sales and keep customers happy. However, verifying compliance of real shelves to the ideal layout is a costly task routinely performed by the store personnel. In this paper, we propose a computer vision pipeline to recognize products on shelves and verify compliance to the planned layout. We deploy local invariant features together with a novel formulation of the product recognition problem as a sub-graph isomorphism between the items appearing in the given image and the ideal layout. This allows for auto-localizing the given image within the aisle or store and improving recognition dramatically.
Keywords
Cite
@article{arxiv.1707.08378,
title = {Product recognition in store shelves as a sub-graph isomorphism problem},
author = {Alessio Tonioni and Luigi Di Stefano},
journal= {arXiv preprint arXiv:1707.08378},
year = {2017}
}
Comments
Slightly extended version of the paper accepted at ICIAP 2017. More information @project_page --> http://vision.disi.unibo.it/index.php?option=com_content&view=article&id=111&catid=78