A comprehensive survey on computer vision based approaches for automatic identification of products in retail store

Article Type

Research Article

Publication Title

Image and Vision Computing

Abstract

The ability to recognize a product on the shelf of a retail store is an ordinary human skill. The same recognition problem presents an exceptional challenge for machine vision systems. Automatic detection of products on the shelf of a retail store provides enhanced value-added consumer experience and commercial benefits to retailers. Compared to machine vision based object recognition system, automatic detection of retail products in a store setting has lesser number of successful attempts. In this paper, we present a survey of machine vision based retail product recognition system and define a new taxonomy for this field. We also describe the intrinsic challenges associated with the problem. In this comprehensive survey of published papers, we analyze features used in state-of-the-art attempts. The performances of these approaches are compared. The details of publicly available datasets are presented. The paper concludes pointing to possible directions of research in related fields.

First Page

45

Last Page

63

DOI

10.1016/j.imavis.2019.03.005

Publication Date

6-1-2019

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