Clothing Genre Classification by Exploiting the Style Elements
碩士 === 國立臺灣科技大學 === 資訊工程系 === 100 === This study presents a novel approach to automatically detect clothing genre from a full-body input image with no restrictions of people poses, races, genders, ages, image backgrounds, and image resolutions. We have identified five style elements for distinguishi...
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ndltd-TW-100NTUS53920762019-05-15T20:51:11Z http://ndltd.ncl.edu.tw/handle/8vxsp5 Clothing Genre Classification by Exploiting the Style Elements 利用服裝樣式元素的服裝分類器 Shintami Chusnul Hidayati 辛大美 碩士 國立臺灣科技大學 資訊工程系 100 This study presents a novel approach to automatically detect clothing genre from a full-body input image with no restrictions of people poses, races, genders, ages, image backgrounds, and image resolutions. We have identified five style elements for distinguishing eight kinds of upperwear genres and seven style elements for distinguishing eight kinds of lowerwear genres. These style elements are identified based on the clothing design theory. The corresponding features for each style elements are also designed. For extracting these style elements, in the proposed frameworks, we first employ an upper-body detector to get body parts of a person standing arbitrary pose in images. The extracted feature vectors of the style elements are then exploited for learning the genre models and used for predicting the clothing genre. We illustrated the effectiveness of our approach by showing the achieved precision, recall, and F-score. For upperwear genres detection, we achieved overall precision of 92.04%, recall of 92.45%, and F-score of 92.25%. And for lowerwear genres detection, we achieved overall precision of 94.66%, recall of 93.64%, and F-score of 94.15%. Kai-Lung Hua 花凱龍 2012 學位論文 ; thesis 52 en_US |
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碩士 === 國立臺灣科技大學 === 資訊工程系 === 100 === This study presents a novel approach to automatically detect clothing genre from a full-body input image with no restrictions of people poses, races, genders, ages, image backgrounds, and image resolutions. We have identified five style elements for distinguishing eight kinds of upperwear genres and seven style elements for distinguishing eight kinds of lowerwear genres. These style elements are identified based on the clothing design theory. The corresponding features for each style elements are also designed. For extracting these style elements, in the proposed frameworks, we first employ an upper-body detector to get body parts of a person standing arbitrary pose in images. The extracted feature vectors of the style elements are then exploited for learning the genre models and used for predicting the clothing genre. We illustrated the effectiveness of our approach by showing the achieved precision, recall, and F-score. For upperwear genres detection, we achieved overall precision of 92.04%, recall of 92.45%, and F-score of 92.25%. And for lowerwear genres detection, we achieved overall precision of 94.66%, recall of 93.64%, and F-score of 94.15%.
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author2 |
Kai-Lung Hua |
author_facet |
Kai-Lung Hua Shintami Chusnul Hidayati 辛大美 |
author |
Shintami Chusnul Hidayati 辛大美 |
spellingShingle |
Shintami Chusnul Hidayati 辛大美 Clothing Genre Classification by Exploiting the Style Elements |
author_sort |
Shintami Chusnul Hidayati |
title |
Clothing Genre Classification by Exploiting the Style Elements |
title_short |
Clothing Genre Classification by Exploiting the Style Elements |
title_full |
Clothing Genre Classification by Exploiting the Style Elements |
title_fullStr |
Clothing Genre Classification by Exploiting the Style Elements |
title_full_unstemmed |
Clothing Genre Classification by Exploiting the Style Elements |
title_sort |
clothing genre classification by exploiting the style elements |
publishDate |
2012 |
url |
http://ndltd.ncl.edu.tw/handle/8vxsp5 |
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