Jul 2026· The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences· Vol XLIX-B1-2026, pp. 239-246· 0 citations· 12 references
Abstract
Abstract. Small-format multi-head camera systems are increasingly deployed for UAV-based 3D mapping; however, systematic evaluations that explicitly link acquisition geometry to network robustness and façade reconstruction completeness remain scarce. This study establishes a geometry-driven, multi-dataset evaluation framework to assess such systems in topographic mapping. Six UAV datasets with varying flying altitudes, overlaps, platforms, cameras, and urbanization are analyzed using a rigorous bundle block adjustment workflow. Internal network strength is quantified using image connectivity, image ray intersection angles, and tie point multiplicity, while object-space accuracy is assessed using ground control point residuals. Reconstruction completeness is evaluated using façade-specific point density metrics, enabling a controlled comparison between nadir-only and multi-head (nadir + oblique) configurations. The results show that oblique imagery strengthens multi-directional image network geometry and substantially improves façade reconstruction. This study establishes empirical relationships between acquisition design, network stability, and object-space completeness.
A monocular 3D localization framework using a prebuilt, georegistered triangular mesh using a two-dimensional grid indexes the mesh, and a progressive multi-scale strategy loads high-resolution blocks for ray–mesh intersection.
Yan-Xin Sun, Ming-Ming Ma, Lan-Yu Sun et al.· Electronics· 0 citations
Accurate registration between aerial imagery and LiDAR point clouds is fundamental to building-level analysis and urban modeling. Although coarse alignment can be achieved through geo-referencing or sensor calibration, residual misalignment often remains and affects the reliable interpretation of roof structures. To ad...
Qi-Peng Mei, D. Bulatov, D. Iwaszczuk· The International Archives o...· 0 citations
GeoFF3D reconstructs 2,000 images in approximately five minutes, demonstrating scalable and robust large-scale UAV reconstruction, which combines a coordinate-anchored model with a spatial large-scale reconstruction framework (SLRF).
Xiang-Hui Yang, Yongli Wang, Yunsheng Zhang et al.· 1 citation
Results indicate that the proposed enhanced detection algorithm built upon the PointPillars framework can effectively improve the detection accuracy and robustness of LiDAR-based 3D object detection in complex environments.
Yu Zhai, Sen Xie, Wen-Hao Li et al.· Electronics· 0 citations
This study presents a pipeline for constructing an HD-map-referenced three-dimensional point cloud in an absolute coordinate system from a single low-cost monocular driving video and demonstrates a practical low-cost route for constructing spatial data in GNSS-denied road sections.
Jun-Su Kim, Yo-Han Han, Eun-Joo Suk et al.· GEO DATA· 0 citations
Aiming at the problem of high data demand for three-dimensional (3D) reconstruction based on a single data source, a large-scale scene 3D reconstruction method using crowdsourced images is proposed. Firstly, dense point clouds are extracted from satellite images and aerial images respectively. For satellite images, den...
Xiao-Wei Chen, Xin Zhou, Qiang Zhang et al.· International Conference on...· 0 citations
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