A Robust and Effective Identification Method for Point-Distributed Coded Targets in Digital Close-Range Photogrammetry

• Published in: Remote sensing (Basel, Switzerland) Switzerland), 2022-11, Vol.14 (21), p.5377
• Main Authors: Wang, Qiang, Liu, Yang, Guo, Yuhan, Wang, Shun, Zhang, Zhenxin, Cui, Ximin, Zhang, Hu
• Format: Article
• Language: English
• Subjects: Accuracy; Aerial photography; Affine transformations; Cameras; coplanar P2-invariant; Deep learning; Design; Diameters; GSI coded target; Identification; Identification methods; Libraries; Matching; Methods; Photogrammetry; Stars; Triangulation; UAV; Unmanned aerial vehicles; Viewing; Vision systems
• ISSN: 2072-4292; 2072-4292
• DOI: 10.3390/rs14215377

In close-range or unmanned aerial vehicle (UAV) photogrammetry, Schneider concentric circular coded targets (SCTs), which are public, are widely used for image matching and as ground control points. GSI point-distributed coded targets (GCTs), which are only mainly applied in a video-simultaneous triangulation and resection system (V-STARS), are non-public and rarely applied in UAV photogrammetry. In this paper, we present our innovative detailed solution to identify GCTs. First, we analyze the structure of a GCT. Then, a special 2D P2-invariant of five coplanar points derived from cross ratios is adopted in template point registration and identification. Finally, the affine transformation is used for decoding. Experiments indoors—including different viewing angles ranging from 0° to 80° based on 6 mm-diameter GCTs, smaller 3 mm-diameter GCTs, and different sizes mixed—and outdoors with challenging scenes were carried out. Compared with V-STARS, the results show that the proposed method can preserve the robustness and achieves a high accuracy rate in identification when the viewing angle is not larger than 65° through indoor experiments, and the proposed method can achieve approximate or slightly weaker effectiveness than V-STARS on the whole. Finally, we attempted to extend and apply the designed GCTs in UAV photogrammetry for a preliminary experiment. This paper demonstrates that GCTs can be designed, printed, and identified easily through our method. It is expected that the proposed method may be helpful when applied to image matching, camera calibration, camera orientation, or 3D measurements or serving as control points in UAV photogrammetry for scenarios with complex structures in the future.