Fast Iterative Closest Point Framework for 3D LIDAR data in Intelligent Vehicle

被引：0
|
作者：
Choi, Won-Seok [1 ]
Kim, Yang-Shin [1 ]
Oh, Se-Young [1 ]
Lee, Jeihun [2 ]
机构：
[1] Pohang Univ Sci & TECHnol POSTECH, Dept Elect Engn, Pohang, South Korea
[2] LG Elect Inc, IT Lab, Seoul, South Korea
来源：
2012 IEEE INTELLIGENT VEHICLES SYMPOSIUM (IV) | 2012年
关键词：
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
The Iterative Closest Point (ICP) algorithm is one of the most popular methods for geometric alignment of 3-dimensional data points. We focus on how to make it faster for 3D range scanner in intelligent vehicle. The ICP algorithm mainly consists of two parts: nearest neighbor search and estimation of transformation between two data sets. The former is the most time consuming process. Many variants of the k-d trees have been introduced to accelerate the search. This paper presents a remarkably efficient search procedure, exploiting two concepts of approximate nearest neighbor and local search. Consequently, the proposed algorithm is about 24 times faster than the standard k-d tree.
引用
收藏
页码：1029 / 1034
页数：6
相关论文
共 50 条
  • [1] Iterative Closest Normal Point for 3D Face Recognition
    Mohammadzade, Hoda
    Hatzinakos, Dimitrios
    IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2013, 35 (02) : 381 - 397
  • [2] Compression of dynamic 3D geometry data using iterative closest point algorithm
    Gupta, S
    Sengupta, K
    Kassim, AA
    COMPUTER VISION AND IMAGE UNDERSTANDING, 2002, 87 (1-3) : 116 - 130
  • [3] A Modified Iterative Closest Point Algorithm for 3D Point Cloud Registration
    Marani, Roberto
    Reno, Vito
    Nitti, Massimiliano
    D'Orazio, Tiziana
    Stella, Ettore
    COMPUTER-AIDED CIVIL AND INFRASTRUCTURE ENGINEERING, 2016, 31 (07) : 515 - 534
  • [4] 3D Visual SLAM Based on Multiple Iterative Closest Point
    Li, Chunguang
    Tao, Chongben
    Liu, Guodong
    MATHEMATICAL PROBLEMS IN ENGINEERING, 2015, 2015
  • [5] Automated Aerial Refueling: Parallelized 3D Iterative Closest Point
    Piekenbrock, Matt
    Robinson, Jace
    Burchett, Lee
    Nykl, Scott
    Woolley, Brian
    Terzuoli, Andrew
    PROCEEDINGS OF THE 2016 IEEE NATIONAL AEROSPACE AND ELECTRONICS CONFERENCE (NAECON) AND OHIO INNOVATION SUMMIT (OIS), 2016, : 188 - 192
  • [6] Fast and Robust Iterative Closest Point
    Zhang, Juyong
    Yao, Yuxin
    Deng, Bailin
    IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE, 2022, 44 (07) : 3450 - 3466
  • [7] 3D Face Recognition Based on Fast Feature Detection and Non-rigid Iterative Closest Point
    Tong, Can
    Kamata, Sei-ichiro
    Ahrary, Alireza
    2009 IEEE INTERNATIONAL CONFERENCE ON INTELLIGENT COMPUTING AND INTELLIGENT SYSTEMS, PROCEEDINGS, VOL 4, 2009, : 509 - +
  • [8] A New Robust and Fast Iterative Closest Point Algorithm for 3D Ship Hull Plate Bending Machines
    Liu, Xin
    Hu, Yong
    Xiao, Changshi
    JOURNAL OF COASTAL RESEARCH, 2019, : 264 - 268
  • [9] Maize Point Cloud Data Filtering Algorithm Based on Vehicle 3D LiDAR
    Zhang M.
    Miao Y.
    Qiu R.
    Ji Y.
    Li H.
    Li M.
    Nongye Jixie Xuebao/Transactions of the Chinese Society for Agricultural Machinery, 2019, 50 (04): : 170 - 178
  • [10] VEHICLE COMPLETION IN TRAFFIC SCENE USING 3D LIDAR POINT CLOUD DATA
    Wu, Chongrong
    Lin, Yitai
    Guo, Yan
    Wen, Chenglu
    Shi, Yongfei
    Wang, Cheng
    2022 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS 2022), 2022, : 7495 - 7498
12345