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首页> 外文会议>2016 World Conference on Futuristic Trends in Research and Innovation for Social Welfare >New improved image registration based tracking system
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New improved image registration based tracking system

机译：新型改进的基于图像配准的跟踪系统

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摘要

This paper gives the information about object matching and tracking has found important and wide applications. An object matching and tracking algorithm based on SURF (Speeded-Up Robust Feature) method is presented in this project. In existing system the SIFT (Scale-Invariant Feature Transform) method is used which have some problems like time complexity, feature extraction, occlusion problem. To overcome these problems SURF method will be used in this project. Firstly, feature points are extracted respectively from base image using SURF method. Then, a coarse-to-fine matching method is used to realize the match of SURF feature points. It shows that, compared with the frequently-used normal cross correlation method, the presented algorithm can process more complicated geometric deformations existed between images and gives high matching accuracy as compare to the matching algorithm based on SIFT feature, in the presented algorithm the processing speed is faster than other algorithm and also lower computational burden, which can meet the real-time requirements for object matching and tracking.
机译：本文给出的有关对象匹配和跟踪的信息已发现重要且广泛的应用。该项目提出了一种基于SURF（快速鲁棒特征）方法的目标匹配与跟踪算法。在现有系统中，使用SIFT（尺度不变特征变换）方法，该方法存在一些问题，例如时间复杂度，特征提取，遮挡问题。为了克服这些问题，本项目将使用SURF方法。首先，利用SURF方法分别从基础图像中提取特征点。然后，采用从粗到精的匹配方法实现SURF特征点的匹配。结果表明，与基于SIFT特征的匹配算法相比，与常用的正交互相关方法相比，该算法可以处理图像之间存在的更复杂的几何变形，并具有较高的匹配精度。与其他算法相比，速度更快，运算量也更低，可以满足对象匹配和跟踪的实时要求。

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