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《Journal of Jiamusi University(Natural Science Edition)》 2019-06
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Experimental Study on Influencing Factors of SLAM Visual Feature Point Extraction and Matching

MU Li-li;HE Shi-zheng;GUO Feng;CHEN Kai;YAO Pan-tao;College of Mechanical Engineering, Anhui University of Science and Technology;  
Feature extraction and matching are the most basic visual front-end steps of SLAM for mobile robots, which directly determine the effect of SLAM location and mapping. In order to verify the impact of environmental changes on different feature points extraction and matching rate, the RANSAC strategy is used to eliminate mismatching. Then the matching effects of SIFT, SURF and ORB feature points are studied from the perspectives of illumination intensity, image rotation, image blurring, scale change and image weak texture. Experiments show that ORB feature points complete the matching between images with the fastest speed, high robustness to environmental changes, good operational performance and matching characteristics, and it is an ideal front-end visual feature point selection.
【CateGory Index】: TP391.41;TP242
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【Citations】
Chinese Journal Full-text Database 2 Hits
1 LIANG Qiu-yan;GE Yi-yuan;NIU Guo-ling;College of Mechanical Engineering,Jiamusi University;;Design of Intelligent Blind Cane Based on Visual Monitoring[J];佳木斯大学学报(自然科学版);2015-04
2 WANG Zhongli;ZHAO Jie;CAI Hegao;School of Electronic and Information Engineering,Beijing Jiaotong University;State Key Laboratory of Robotics and System,Harbin Institute of Technology;;A survey of front-end method for graph-based slam under large-scale environment[J];哈尔滨工业大学学报;2015-01
【Co-citations】
Chinese Journal Full-text Database 1 Hits
1 WANG Zhongli;ZHAO Jie;CAI Hegao;School of Electronic and Information Engineering,Beijing Jiaotong University;State Key Laboratory of Robotics and System(Harbin Institute of Technology);;A survey of back-end optimization method for graph-based SLAM under large-scale environment[J];哈尔滨工业大学学报;2015-07
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Chinese Journal Full-text Database 6 Hits
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