Brand Recognition with Partial Visible Image in the Bottle Random Picking Task based on Inception V3

研究成果: Conference contribution

抄録

In the brand-wise random-ordered drinking PET bottles picking task, the overlapping and viewing angle problem makes a low accuracy of the brand recognition. In this paper, we set the problem to increase the brand recognition accuracy and try to find out how the overlapping rate infects on the recognition accuracy. By using a stepping motor and transparent fixture, the training images were taken automatically from the bottles under 360 degrees to simulate a picture taken from viewing angle. After that, the images are augmented with random cropping and rotating to simulate the overlapping and rotation in a real application. By using the automatically constructed dataset, the Inception V3, which was transferred learning from ImageNet, is trained for brand recognition. By generating a random mask with a specific overlapping rate on the original image, the Inception V3 can give 80% accuracy when 45% of the object in the image is visible or 86% accuracy when the overlapping rate is lower than 30%.

本文言語English
ホスト出版物のタイトル2019 28th IEEE International Conference on Robot and Human Interactive Communication, RO-MAN 2019
出版社Institute of Electrical and Electronics Engineers Inc.
ISBN(電子版)9781728126227
DOI
出版ステータスPublished - 2019 10
イベント28th IEEE International Conference on Robot and Human Interactive Communication, RO-MAN 2019 - New Delhi, India
継続期間: 2019 10 142019 10 18

出版物シリーズ

名前2019 28th IEEE International Conference on Robot and Human Interactive Communication, RO-MAN 2019

Conference

Conference28th IEEE International Conference on Robot and Human Interactive Communication, RO-MAN 2019
CountryIndia
CityNew Delhi
Period19/10/1419/10/18

ASJC Scopus subject areas

  • Artificial Intelligence
  • Human-Computer Interaction
  • Control and Optimization

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