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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。所提出的解决方案加入了几种复杂的计算机视觉方法,例如使用adaboost策略,人体分割和使用图形结构和外观模型进行分解的面部检测,以及采用简化的主色描述符的视觉描述符。必须在受控环境中拍摄输入图像,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类似的服装风格的图像。潜在的应用是社交网络服务领域,主要是推荐的基于Web的系统,帮助人们选择衣服和与服装思想分享。已开发的算法已经过650张图像,从互联网中的各种社交媒体收集并显示出高精度。

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