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

机译:对基于计算机视觉的零售商店中产品自动识别方法的全面调查

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摘要

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. (C) 2019 Elsevier B.V. All rights reserved.
机译:识别零售商店货架上的产品的能力是普通的人类技能。相同的识别问题对机器视觉系统提出了特殊的挑战。自动检测零售商店货架上的产品可为零售商提供增强的增值消费者体验和商业利益。与基于机器视觉的对象识别系统相比,在商店环境中自动检测零售产品的成功尝试次数较少。在本文中,我们对基于机器视觉的零售产品识别系统进行了调查,并为此领域定义了新的分类法。我们还将描述与问题相关的内在挑战。在对已发表论文的全面调查中,我们分析了最新尝试中使用的功能。比较了这些方法的性能。列出了公开可用的数据集的详细信息。本文总结指出了相关领域研究的可能方向。 (C)2019 Elsevier B.V.保留所有权利。

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