Image recognition approach for expediting chinese cafeteria checkout process
學年 108
學期 2
發表日期 2020-03-10
作品名稱 Image recognition approach for expediting chinese cafeteria checkout process
作品名稱（其他語言）
著者 B.-T. Wu; Y.-W. Tsou; E. Tan; F.-C. Chang
作品所屬單位
出版者
會議名稱 2020 IEEE 2nd Global Conference on Life Sciences and Technologies (LifeTech)
會議地點 Kyoto, Japan
摘要 One of the common running themes in modern-day Chinese cafeterias is the hold up in foot traffic in queueing due to checkout. We find out that this bottleneck is caused by the staff requiring extra time to look up the prices of those miscellaneous entrees and calculating the total due amount during checkout. In this paper, this issue is addressed by introducing real-time image recognition techniques into this process. By using a webcam taking live video feed at the checkout desk with the image recognition model outputs the total due amount simultaneously, we are able to eliminate the need to perform manual price calculations. Additionally, the nutrition facts of the meal can also be calculated and displayed to the customers based on the detected entrees. The image recognition model is based on YOLOv3 with 575 entree-catered plate images involved in model training, validation, and testing. The transfer learning technique is also incorporated to speed up the training process. Experimental results show that the recognition accuracy of individual entree is around 70% and that of the entire plate is roughly 63%. With the advanced training with a larger dataset, we believe that the accuracy can be increased, and applying the approach during the checkout will become more practicable.
關鍵字 food recognition;automatic price calculation;nutrition facts calculation;object detection;YOLOv3;image recognition;machine learning;transfer learning
語言 en
收錄於
會議性質 國際
校內研討會地點 無
研討會時間 20200310~20200312
通訊作者
國別 JPN
公開徵稿
出版型式
出處
相關連結

機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/118718 )

SDGS 優質教育,產業創新與基礎設施