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Outfit classification and recommendation based on integrated features and bagged decision tree

Outfit classification and recommendation is increasingly important with the rapid growth of user. It is often hard to manage our clothes, especially when we are having too many of them. Sometimes, this could be to the extent where we might even forget the existence of certain clothes that we have. B...

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Main Authors: Mustaffa, Mas Rina, Ong, Soo Feng, Mohd Norowi, Noris, Hussin, Masnida
Format: Article
Language:English
Published: IAEME Publication 2020
Online Access:http://psasir.upm.edu.my/id/eprint/87034/1/Outfit%20classification%20and%20recommendation%20based%20on%20integrated%20features.pdf
http://psasir.upm.edu.my/id/eprint/87034/
https://iaeme.com/Home/article_id/IJARET_11_12_132
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spelling my.upm.eprints.870342022-09-05T02:38:58Z http://psasir.upm.edu.my/id/eprint/87034/ Outfit classification and recommendation based on integrated features and bagged decision tree Mustaffa, Mas Rina Ong, Soo Feng Mohd Norowi, Noris Hussin, Masnida Outfit classification and recommendation is increasingly important with the rapid growth of user. It is often hard to manage our clothes, especially when we are having too many of them. Sometimes, this could be to the extent where we might even forget the existence of certain clothes that we have. Besides that, some of us may face some decision difficulties in pairing suitable outfit for the day due to poor color coordination or styling knowledge. The objective of this work is to introduce a clothes classification and outfit recommendation framework. We first construct the color information of the clothes by extracting and calculating the mean of the RGB color space. Shape representation is obtained by constructing several shape signatures. These contentbased representations are then trained by Bagged Decision Tree for clothes classification. Through color and shape-based matching, the framework can then recommend suitable top or bottom clothing to a user when given a clothes image as the query. We have conducted classification accuracy experiment and user-acceptance testing. Positive results have been obtained for both evaluation approaches. IAEME Publication 2020 Article PeerReviewed text en http://psasir.upm.edu.my/id/eprint/87034/1/Outfit%20classification%20and%20recommendation%20based%20on%20integrated%20features.pdf Mustaffa, Mas Rina and Ong, Soo Feng and Mohd Norowi, Noris and Hussin, Masnida (2020) Outfit classification and recommendation based on integrated features and bagged decision tree. International Journal of Advanced Research in Engineering and Technology, 11 (12). 1400 - 1409. ISSN 0976-6480; ESSN: 0976-6499 https://iaeme.com/Home/article_id/IJARET_11_12_132
institution Universiti Putra Malaysia
building UPM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Putra Malaysia
content_source UPM Institutional Repository
url_provider http://psasir.upm.edu.my/
language English
description Outfit classification and recommendation is increasingly important with the rapid growth of user. It is often hard to manage our clothes, especially when we are having too many of them. Sometimes, this could be to the extent where we might even forget the existence of certain clothes that we have. Besides that, some of us may face some decision difficulties in pairing suitable outfit for the day due to poor color coordination or styling knowledge. The objective of this work is to introduce a clothes classification and outfit recommendation framework. We first construct the color information of the clothes by extracting and calculating the mean of the RGB color space. Shape representation is obtained by constructing several shape signatures. These contentbased representations are then trained by Bagged Decision Tree for clothes classification. Through color and shape-based matching, the framework can then recommend suitable top or bottom clothing to a user when given a clothes image as the query. We have conducted classification accuracy experiment and user-acceptance testing. Positive results have been obtained for both evaluation approaches.
format Article
author Mustaffa, Mas Rina
Ong, Soo Feng
Mohd Norowi, Noris
Hussin, Masnida
spellingShingle Mustaffa, Mas Rina
Ong, Soo Feng
Mohd Norowi, Noris
Hussin, Masnida
Outfit classification and recommendation based on integrated features and bagged decision tree
author_facet Mustaffa, Mas Rina
Ong, Soo Feng
Mohd Norowi, Noris
Hussin, Masnida
author_sort Mustaffa, Mas Rina
title Outfit classification and recommendation based on integrated features and bagged decision tree
title_short Outfit classification and recommendation based on integrated features and bagged decision tree
title_full Outfit classification and recommendation based on integrated features and bagged decision tree
title_fullStr Outfit classification and recommendation based on integrated features and bagged decision tree
title_full_unstemmed Outfit classification and recommendation based on integrated features and bagged decision tree
title_sort outfit classification and recommendation based on integrated features and bagged decision tree
publisher IAEME Publication
publishDate 2020
url http://psasir.upm.edu.my/id/eprint/87034/1/Outfit%20classification%20and%20recommendation%20based%20on%20integrated%20features.pdf
http://psasir.upm.edu.my/id/eprint/87034/
https://iaeme.com/Home/article_id/IJARET_11_12_132
_version_ 1743108539288649728
score 13.211869

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