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

机译:基于计算机视觉的综合调查,零售商店自动识别产品的方法

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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:识别零售店架子上的产品的能力是普通的人力技能。相同的识别问题为机器视觉系统提供了卓越的挑战。零售店架子上的产品自动检测为零售商提供了增强的增值消费者体验和商业益处。与基于机器视觉的物体识别系统相比,在商店设置中的零售产品的自动检测具有较少的成功尝试。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,并为此字段定义了新的分类法。我们还描述了与问题相关的内在挑战。在对发表论文的综合调查中,我们分析了最先进的尝试中使用的功能。比较这些方法的性能。提出了公开的数据集的详细信息。本文的结论指出了相关领域的研究方向。 (c)2019 Elsevier B.v.保留所有权利。

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