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 r...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.展开更多
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).
文摘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.
