Abstract
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.
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