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Comparing Clothing Styles by Means of Computer Vision Methods

机译:通过计算机视觉方法比较服装款式

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The paper deals with a problem of comparing and retrieving visual data representing various clothing styles. Proposed solution joins several sophisticated computer vision methods, such as face detection using AdaBoost strategy, human body segmentation and decomposition using pictorial structures and appearance models, together with visual descriptors employing simplified dominant color descriptor. The input images do not necessary have to be taken in controlled environment, so the flexibility of the system is high. The proposed algorithm makes it possible to compare images presenting humans and retrieve images with similar clothing style. The potential application is the area of social network services, mostly recommendation web-based systems, that help people choose clothes and share with clothing ideas. Developed algorithm has been tested on 650 images gathered from various social media in the Internet and showed high accuracy rate.
机译:本文涉及比较和检索代表各种服装样式的视觉数据的问题。提出的解决方案结合了多种复杂的计算机视觉方法,例如使用AdaBoost策略的面部检测,使用图片结构和外观模型的人体分割和分解,以及使用简化显性色彩描述符的视觉描述符。输入图像不必在受控环境中拍摄,因此系统的灵活性很高。所提出的算法使得可以比较呈现人类的图像并检索具有相似服装风格的图像。潜在的应用程序是社交网络服务领域,主要是基于Web的推荐系统,可帮助人们选择衣服并与衣服创意分享。对从互联网上各种社交媒体收集的650张图像进行了测试的开发算法,显示出很高的准确率。

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