Search by image : clothing segmentation and retrieval

Our study aims to develop a product retrieval system for clothing items. More specifically, we formulate our task as a cross-domain content based image retrieval problem. Product search using traditional keyword matching can be inefficient and time- consuming due to the large semantic gap between l...

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書目詳細資料
主要作者: Shi, Ganyu
其他作者: Lin Guosheng
格式: Final Year Project
語言:English
出版: 2019
主題:
在線閱讀:http://hdl.handle.net/10356/76912
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機構: Nanyang Technological University
語言: English
實物特徵
總結:Our study aims to develop a product retrieval system for clothing items. More specifically, we formulate our task as a cross-domain content based image retrieval problem. Product search using traditional keyword matching can be inefficient and time- consuming due to the large semantic gap between low-level visual features such as shape and colors, and high-level intents of customers. Our system aims to bridge the gap between shoppers and retailers by offering a street-to-shop image retrieval system that supports searching by images. We divide our system into two main stages: 1) Segmentation: We segment the query image into individual clothing classes, and use them as regions of interest for subsequent retrieval. 2) Retrieval: For each of the clothing item, we use image retrieval techniques to fetch visually similar products. We show that, by training effective CNN models, our system achieves fast and accurate clothing retrieval result, and is able to handle challenging scenarios such as diverse viewpoints, occlusion, and complex background.