An intelligent self-checkout system for smart retail

Bing-Fei Wu*, Wan Ju Tseng, Yung Shin Chen, Shih Jhe Yao, Po Ju Chang

*Corresponding author for this work

研究成果: Conference contribution同行評審

2 引文 斯高帕斯(Scopus)

摘要

Most of current self-checkout systems rely on barcodes, RFID tags, or QR codes attached on items to distinguish products. This paper proposes an Intelligent Self-Checkout System (ISCOS) embedded with a single camera to detect multiple products without any labels in real-time performance. In addition, deep learning skill is applied to implement product detection, and data mining techniques construct the image database employed as training dataset. Product information gathered from a number of markets in Taiwan is utilized to make recommendation to customers. The bounding boxes are annotated by background subtraction with a fixed camera to avoid time-consuming process for each image. The contribution of this work is to combine deep learning and data mining approaches to real-time multi-object detection in image-based checkout system.

原文English
主出版物標題2016 IEEE International Conference on System Science and Engineering, ICSSE 2016
發行者Institute of Electrical and Electronics Engineers Inc.
ISBN(電子)9781467389662
DOIs
出版狀態Published - 24 八月 2016
事件2016 IEEE International Conference on System Science and Engineering, ICSSE 2016 - Puli, Taiwan
持續時間: 7 七月 20169 七月 2016

出版系列

名字2016 IEEE International Conference on System Science and Engineering, ICSSE 2016

Conference

Conference2016 IEEE International Conference on System Science and Engineering, ICSSE 2016
國家Taiwan
城市Puli
期間7/07/169/07/16

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