Object tracking method based on joint global and local feature descriptor of 3D LIDAR point cloud  

作　　者：Qishu Qian Yihua Hu Nanxiang Zhao Minle Li Fucai Shao Xinyuan Zhang 钱其姝;胡以华;赵楠翔;李敏乐;邵福才;张鑫源(State Key Laboratory of Pulsed Power Laser Technology,National University of Defense Technology,Hefei 230037,China;Anhui Provincial Key Laboratory of Electronic Restriction,National University of Defense Technology,Hefei 230037,China;The Military Representative Bureau of the Ministry of Equipment Development,Central Military Commission in Beijing,Beijing 100191,China)

机构地区：[1]State Key Laboratory of Pulsed Power Laser Technology,National University of Defense Technology,Hefei 230037,China [2]Anhui Provincial Key Laboratory of Electronic Restriction,National University of Defense Technology,Hefei 230037,China [3]The Military Representative Bureau of the Ministry of Equipment Development,Central Military Commission in Beijing,Beijing 100191,China

出　　处：《Chinese Optics Letters》2020年第6期24-29,共6页中国光学快报（英文版）

基　　金：This work was supported by the National Natural Science Foundation of China(Nos.61271353 and 61871389);Foundation of State Key Laboratory of Pulsed Power Laser Technology(No.SKL2018ZR09);Major Funding Projects of National University of Defense Technology(No.ZK18-01-02).

摘　　要：To fully describe the structure information of the point cloud when the LIDAR-object distance is long,a joint global and local feature(JGLF)descriptor is constructed.Compared with five typical descriptors,the object recognition rate of JGLF is higher when the LIDAR-object distances change.Under the situation that airborne LIDAR is getting close to the object,the particle filtering(PF)algorithm is used as the tracking frame.Particle weight is updated by comparing the difference between JGLFs to track the object.It is verified that the proposed algorithm performs 13.95%more accurately and stably than the basic PF algorithm.

关 键 词：object tracking LIDAR global and local feature descriptor point cloud 

分 类 号：TN958.98[电子电信—信号与信息处理]