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Location of Object Based on Local Feature Descriptor

DENG Jihong;WEI Yuxing;Institute of Optics Electronics, Chinese Academy of Sciences;University of Chinese Academy of Sciences;  
The existing local feature descriptors, such as SURF and BRISK, either cannot meet the real-time or have poor performance, so the paper presents a novel descriptor SURF-BRISK. The descriptor detects the Key-points by SURF and computes the descriptor by BRISK. Firstly, our method is used to do feature matching. Then RANSAC robust estimation is performed to eliminate the wrong matched points. Finally, location of object is based on the affine transform's six parameters which are calculated by the correct matches. Experiments show that SURF-BRISK feature descriptor is not only real-time and robustness, but also achieves good results in object location.
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