ARC：一个基于视觉的自动零售收银系统
ARC: A Vision-based Automatic Retail Checkout System
摘要：
超市采用的零售结账系统主要依赖于条形码扫描仪，其中一些使用QR码来识别所购买的物品。这些方法在实践中是耗时的，需要一定程度的人工监督，并且需要排长队等待。在这方面，我们提出了一个系统，我们称之为ARC，旨在使零售商店柜台的结账过程更快，更自主，更方便，同时减少对人类操作员的依赖。该方法利用了一个基于计算机视觉的系统，其核心是一个卷积神经网络，它扫描放置在网络摄像头下的物体进行识别。为了评估所提出的系统，我们策划了一个包含100个不同类别的本地零售项目的图像数据集。在给定的假设和考虑范围内，该系统实现了合理的测试时间精度，为拟议的设置指明了一个雄心勃勃的未来。项目代码和数据集是公开的。
英文摘要：
Retail checkout systems employed at supermarkets primarily rely on barcode scanners, with some utilizing QR codes, to identify the items being purchased. These methods are time-consuming in practice, require a certain level of human supervision, and involve waiting in long queues. In this regard, we propose a system, that we call ARC, which aims at making the process of check-out at retail store counters faster, autonomous, and more convenient, while reducing dependency on a human operator. The approach makes use of a computer vision-based system, with a Convolutional Neural Network at its core, which scans objects placed beneath a webcam for identification. To evaluate the proposed system, we curated an image dataset of one-hundred local retail items of various categories. Within the given assumptions and considerations, the system achieves a reasonable test-time accuracy, pointing towards an ambitious future for the proposed setup. The project code and the dataset are made publicly available.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
