Detection of positions and recognition of brand logos visible on images captured using mobile devices

M. Skoczylas
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引用次数: 3

Abstract

Up till now there does not exist an easy, mobile mechanism that allows to easily capture, recognize and count defined, multiple objects that are visible in surroundings of the user. For this purpose, feature detectors (such as SIFT, SURF or BRISK) are utilized to create a database of products box images and extracted keypoints are stored. Existing algorithms based on keypoints analysis do not allow to identify multiple identical logos, due to the fact that a homography calculated on found keypoints can span two or more objects and the result then can be skewed. In this paper a solution to this problem will be shown, that by using a sliding window that joins multiple found keypoints into individual objects, it is possible to correctly detect multiple identical objects. In this paper preliminary results of a mobile framework that allows recognition and counting of visible products in surroundings of the user will be presented.
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检测位置和识别使用移动设备捕获的图像上可见的品牌标志
到目前为止,还没有一种简单的、可移动的机制,可以轻松地捕获、识别和计数用户周围可见的多个定义对象。为此,利用特征检测器(如SIFT, SURF或BRISK)创建产品盒图像数据库,并存储提取的关键点。基于关键点分析的现有算法不允许识别多个相同的徽标,因为根据发现的关键点计算的单应性可能跨越两个或更多对象,并且结果可能会扭曲。本文将给出一个解决方案,即通过使用滑动窗口将多个找到的关键点连接到单个对象中,可以正确检测多个相同的对象。在本文中,一个移动框架的初步结果,允许识别和计数在用户周围的可见产品将被呈现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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