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《Geomatics and Information Science of Wuhan University》 2013-09
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Linear-Feature-Constrained Registration of LiDAR Point Cloud via Quaternion

WANG Yongbo1,2 YANG Huachao1,2 LIU Yanhua1,2 NIU Xiaonan1,2(1 Key Laboratory for Land Environment & Disaster Monitoring of SBSM,China University of Mining & Technology, 1 Daxue Road,Xuzhou,221116,China)(2 Jiangsu Key Laboratory of Resources and Environmental Information Engineering,China University of Mining & Technology, 1 Daxue Road,Xuzhou,221116,China)  
Considering the large amount of computation low accuracy of extracted point-like features are the two main disadvantages of traditional point-to-point based registration methods which is designed for LiDAR point cloud,and the accuracy of registration results is seriously decreased by the linearization procedure of traditional 7-parameter based transformation approaches,a new registration approach is designed to overcome above disadvantages,which selects linear features as registration primitives,and uses quaternion to represent rotation matrix.Similarity measure of the linear-feature-constrained 3D transformation procedure is presented,and the formulation of registration procedure is exactly deduced.Besides,the detailed procedure of how to calculate rotation,translation scale is also presented.Experiments show that the presented approach is efficient effective.More importantly,by using quaternion to represent rotation matrix,the new presented approach avoids the decrease of accuracy,meanwhile,due to the characteristic of quaternion,it also needs few calculation resources compared to traditional registration methods.
【Fund】: 国家自然科学基金资助项目(41001297 41271444 41001312);; 江苏省自然科学基金资助项目(BK2012569);; 江苏高校优势学科建设工程资助项目;; 中国矿业大学国土环境与灾害监测国家测绘地理信息局重点实验室开放研究基金资助项目(LEDM2010B10)
【CateGory Index】: P225
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