【摘要】：隨著服裝產(chǎn)業(yè)的飛速發(fā)展,通過(guò)計(jì)算機(jī)視覺(jué)技術(shù)解決服裝領(lǐng)域相關(guān)問(wèn)題已經(jīng)成為近年來(lái)的研究熱點(diǎn)。由于服裝款式和服裝風(fēng)格的多樣性與復(fù)雜性很大程度上增加了個(gè)性化服裝推薦的難度,使得目前所擁有的服裝推薦的準(zhǔn)確率仍有待提高。針對(duì)如何實(shí)現(xiàn)能夠推薦最適合用戶膚色、發(fā)色、瞳色及風(fēng)格的服裝,本文提出基于圖像內(nèi)容的服裝分類和推薦方法。針對(duì)服裝款式和風(fēng)格的多樣性與復(fù)雜性,本文提出了一種基于特征提取和距離度量的服裝風(fēng)格分類方法。首先,建立服裝圖像數(shù)據(jù)集;然后,通過(guò)土耳其機(jī)器人對(duì)所有服裝圖像的風(fēng)格、屬性進(jìn)行標(biāo)注;之后,對(duì)所有圖像進(jìn)行姿勢(shì)估計(jì)和特征提取;最后,采用特征提取和距離度量對(duì)多個(gè)服裝屬性標(biāo)簽分類,實(shí)現(xiàn)基于服裝風(fēng)格的服裝分類。針對(duì)已有的服裝推薦算法中服裝色調(diào)與用戶顏色特征不協(xié)調(diào)以及推薦的準(zhǔn)確率不高的問(wèn)題,將服裝搭配的四季色彩理論與計(jì)算機(jī)視覺(jué)領(lǐng)域的推薦方法相結(jié)合,本文還根據(jù)該風(fēng)格分類方法的分類結(jié)果提出一種基于圖像內(nèi)容的服裝推薦方法。首先,提出四季色彩判斷模型,對(duì)根據(jù)輸入的人臉圖像提取得到的用戶顏色特征集進(jìn)行分類;然后,建立優(yōu)化處理模型,根據(jù)四季色彩判斷模型結(jié)果和用戶所需風(fēng)格進(jìn)行優(yōu)化處理并獲得服裝預(yù)推薦結(jié)果;最后,通過(guò)用戶評(píng)分及反饋機(jī)制,提高優(yōu)化結(jié)果,得到最終推薦結(jié)果。實(shí)驗(yàn)表明,本文所提出的基于特征提取和距離度量的服裝風(fēng)格分類方法可以有效地對(duì)不同風(fēng)格的服裝進(jìn)行分類。提出的基于圖像內(nèi)容的服裝推薦方法能夠?qū)崿F(xiàn)與用戶顏色特征相協(xié)調(diào),并且在實(shí)際應(yīng)用中其推薦結(jié)果具有較高的準(zhǔn)確率。
[Abstract]:With the rapid development of garment industry, it has become a research focus in recent years to solve the related problems in clothing field by computer vision technology. Due to the diversity and complexity of fashion styles and styles, the difficulty of personalized clothing recommendation is greatly increased, so the accuracy of clothing recommendation still needs to be improved. In view of how to recommend the most suitable color, hair color, pupil color and style of clothing, this paper proposes a method of clothing classification and recommendation based on image content. In view of the diversity and complexity of fashion styles and styles, this paper presents a method of fashion style classification based on feature extraction and distance measurement. First, the clothing image data set is established; then, the style and attributes of all the clothing images are annotated by the Turkish robot; after that, the pose estimation and feature extraction of all the images are carried out. Finally, feature extraction and distance measurement are used to classify multiple clothing attribute labels to achieve clothing classification based on clothing style. In order to solve the problem that the color features of clothing color and user color are not in harmony and the accuracy of recommendation is not high, the four seasons color theory of clothing collocation is combined with the recommended method in the field of computer vision. According to the classification results of the style classification method, this paper proposes a clothing recommendation method based on image content. Firstly, the four seasons color judgment model is proposed to classify the user color feature set extracted from the input face image. Then, the optimization processing model is established, according to the results of the four seasons color judgment model and the style required by the user, the optimal processing is carried out and the clothing pre-recommendation result is obtained. Finally, through the user rating and feedback mechanism, improve the optimization results and get the final recommendation results. Experimental results show that the proposed method based on feature extraction and distance measurement can effectively classify different styles of clothing. The proposed clothing recommendation method based on image content can coordinate with the color features of users and has a high accuracy in practical application.
【學(xué)位授予單位】：昆明理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TP391.41;TP391.3

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