Efficient Coarse Registration of Pairwise TLS Point Clouds Using Ortho Projected Feature Images
Bibliographic Data
| ID | 22031393 |
|---|---|
| Authors | Hua Liu (0000-0003-2798-3337, East China University of Technology), Xiaoming Zhang (0000-0002-3134-9294, Wuhan University), Yuancheng Xu (0000-0003-3001-2435, East China University of Technology), Xiao-Yong Chen (0000-0002-4795-8940, East China University of Technology, corresponding author), Xiaoyong Chen (0000-0003-0810-9863, East China University of Technology) |
| Year | 2020 |
| Volume | 9 |
| Issue | 4 |
| Pages | 255 |
| Publication date | 2020-04-18 |
| Peer Reviewed | Yes |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | ISPRS International Journal of Geo-Information (JOURNAL) |
| Journal identifiers | ISSN: 2220-9964 • E-ISSN: 2220-9964 |
| Publisher | MDPI AG (PUBLISHER • IT) |
| DOI | 10.3390/ijgi9040255 |
| OpenAlex | W3017084579 |
| Language | EN |
| Citations received | 1 |
| References cited | 43 |
The degree of automation and efficiency are among the most important factors that influence the availability of Terrestrial light detection and ranging (LiDAR) Scanning (TLS) registration algorithms. This paper proposes an Ortho Projected Feature Images (OPFI) based 4 Degrees of Freedom (DOF) coarse registration method, which is fully automated and with high efficiency, for TLS point clouds acquired using leveled or inclination compensated LiDAR scanners. The proposed 4DOF registration algorithm decomposes the parameter estimation into two parts: (1) the parameter estimation of horizontal translation vector and azimuth angle; and (2) the parameter estimation of the vertical translation vector. The parameter estimation of the horizontal translation vector and the azimuth angle is achieved by ortho projecting the TLS point clouds into feature images and registering the ortho projected feature images by Scale Invariant Feature Transform (SIFT) key points and descriptors. The vertical translation vector is estimated using the height difference of source points and target points in the overlapping regions after horizontally aligned. Three real TLS datasets captured by the Riegl VZ-400 and the Trimble SX10 and one simulated dataset were used to validate the proposed method. The proposed method was compared with four state-of-the-art 4DOF registration methods. The experimental results showed that: (1) the accuracy of the proposed coarse registration method ranges from 0.02 m to 0.07 m in horizontal and 0.01 m to 0.02 m in elevation, which is at centimeter-level and sufficient for fine registration; and (2) as many as 120 million points can be registered in less than 50 s, which is much faster than the compared methods
Azimuth · Computer vision · Feature extraction · Geometry · Lidar · Pairwise comparison · Point cloud · Ranging · Remote sensing · Scale-invariant feature transform · 3D Surveying and Cultural Heritage · Computer Science · Mathematics · Remote Sensing and LiDAR Applications · Robotics and Sensor-Based Localization · Artificial Intelligence · Geology
| Unique citing works | 1 |
|---|---|
| Citations per year | 0,2 |
| Citation span | 2021 - 2021 (1) |
| Citation velocity | historical |
| Highly cited | No |
| Citation types | Neutral: 1 |