Clothing Recommendation System based on Visual Information Analytics

Yun Rou Lin, Wei Hsiang Su, Chub Hsien Lin, Bing-Fei Wu, Chang Hong Lin, Hsin Yeh Yang, Ming Yen Chen

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

5 Scopus citations

Abstract

Due to the short fashion style life circle, much more different clothing designs show up. It is hard for consumers to find the suitable clothes effectively. To solve this problem, an automatic and reliable recommendation system is in great demand. In this paper, the clothing attributes recognition, gender recognition, and body height are considered to design the recommendation system. Based on the clothing style, gender and body height, the system can recommend the proper clothes with suitable size. On-line texture modeling is proposed to produce the variation of the clothing texture so that the recommendation system can give reasonable and diversified choices for the consumers. Besides, the data of consumers' wearing style is also useful to make the better marketing strategy. According to the reasons above, the clothing recognition and recommendation system can create a win-win situation between the consumers and the fashion industry.

Original languageEnglish
Title of host publication2019 International Automatic Control Conference, CACS 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781728138466
DOIs
StatePublished - Nov 2019
Event2019 International Automatic Control Conference, CACS 2019 - Keelung, Taiwan
Duration: 13 Nov 201916 Nov 2019

Publication series

Name2019 International Automatic Control Conference, CACS 2019

Conference

Conference2019 International Automatic Control Conference, CACS 2019
Country/TerritoryTaiwan
CityKeelung
Period13/11/1916/11/19

Keywords

  • clothing recognition
  • content-based filtering
  • deep learning
  • recommendation system

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