The paper presents a close‑range photogrammetry workflow using Structure‑from‑Motion and Multi‑View Stereo to generate high‑resolution 3D point clouds of rubberised concrete. By capturing images with a Canon DSLR and an iPhone 16, the authors achieved sub‑millimetre reconstruction accuracy, outperforming traditional LiDAR for fine‑scale defect analysis. An RGB‑guided crack extraction method and deformation analysis further demonstrate the method’s utility for detailed surface monitoring and material performance evaluation.
By Jiacheng Liu, Mohammed Alnahhal, Ailar Hajimohammadi, Sara Gonizzi Barsanti, Jinling Wang, Mohsen Kalantari
arXiv:2512. 09062v2 Announce Type: replace-cross Abstract: Accurate 3D scene interpretation in active construction sites is essential for progress monitoring, safety assessment, and digital twin development.
By Seongyong Kim, Yong Kwon Cho
arXiv:2609.28154v1 Announce Type: new
Abstract: Global building and settlement datasets increasingly support population mapping, exposure assessment, urban monitoring, and other analyses of the built...
By Rufai Omowunmi Balogun, Caroline Margaux Gevaert, Capucine Riom, Derrick Mirindi, Aaron Opdyke, Hamed Alemohammad, Pierre Chrzanowski, Edward Charles Anderson
arXiv:2606. 09882v1 Announce Type: cross Abstract: The paradigm of digital twin cities is shifting from coarse visual mapping toward more precise and actionable digitization of urban assets.
By Chong Liu, Luxuan Fu, Xuyu Feng, Zhen Dong, Bisheng Yang
The paper introduces a novel, training‑free, LLM‑driven closed‑loop framework for fusing dual‑source encrypted points of interest (DSEP) to improve land‑use/land‑cover (LULC) mapping. By iteratively refining location transformations and attribute correspondences—using LLM‑based matching, particle swarm optimization, and fuzzy attribute reassessment—the method reduces matching complexity from O(N²) to O(N) and converges in about two iterations. Experiments across 31 Chinese provincial capitals demonstrate a 4.58 m average location residual and 95.12 % attribute accuracy, outperforming existing baselines by 1.77 m and 14.87 % respectively, and enabling georeferencing of encrypted vector data to WGS‑84 without ground control points.
By Chang Li, Xingtao Peng, Yongjun Zhang, Yinfei He, Cairun Huang
arXiv:2609.37071v1 Announce Type: new
Abstract: Non-rigid point-cloud registration aims to find the corresponding target point for each point on a deforming source surface. Point-level matching keeps...
By Yuzhen He, Sara Homscheid
arXiv:2601. 03569v3 Announce Type: replace Abstract: Local Intrinsic Dimensionality (LID) has shown strong potential for anomaly detection in high-dimensional data, including landslide failure detection in granular media, where early and accurate identification of failure zones is crucial for effective geohazard mitigation.
By Yuansan Liu, James Bailey, Antoinette Tordesillas
arXiv:2510. 21112v3 Announce Type: replace-cross Abstract: High-definition 3D city maps enable city planning and change detection, which is essential for municipal compliance, map maintenance, and asset monitoring, including both built structures and urban greenery.
By Hezam Albaqami, Haitian Wang, Xinyu Wang, Muhammad Ibrahim, Zainy M. Malakan, Abdullah M. Algamdi, Mohammed H. Alghamdi, Ajmal Mian
The paper introduces GMPCR, a non‑learning spectral consistency‑guided framework for multiview point cloud registration in low‑overlap scenes. GMPCR refines initial correspondences into a second‑order compatibility structure, uses spectral analysis to filter unreliable matches and select informative scan pairs, and then applies maximal‑clique hypothesis generation for robust relative transformations. The resulting sparse pose graph is further refined with an adaptive history‑aware synchronization scheme, and a recovery mechanism allows previously down‑weighted edges to regain confidence, achieving high registration recalls on benchmark datasets while reducing computational cost.
By Tianyu Li, Yanghong Lin, Shudong Zhou, Kui Yang, Jingru Zhang, Li Fang, Wei Yao
arXiv:2608. 19522v1 Announce Type: cross Abstract: Scan-to-map LiDAR odometry drifts unboundedly along the unobservable axes of geometrically degenerate environments like tunnels and corridors, and existing degeneracy handling requires environment-specific parameter tuning.
By Eunsoo Im
The paper investigates how processing parameters affect the accuracy of UAV photogrammetry. By testing 768 processing variants on ten datasets over 1.5 years, the study finds that the best configuration yields an RMSE of 16 mm, while the worst reaches 303 mm. Key factors include the number of ground control points, camera calibration corrections, and the use of Post‑Processing Kinematic GNSS for camera center determination, which together reduce systematic errors by more than half.
By Pawe{\l} \'Cwi\k{a}ka{\l}a, Edyta Puniach, El\.zbieta Pastucha, Wojciech Gruszczy\'nski
arXiv:2606.29167v2 Announce Type: replace
Abstract: Dense correspondence on in-the-wild 3D scans must handle severe non-isometric deformation, partial observations, topology artifacts, irregular disc...
By Qilong Liu, Qinfeng Xiao, Chenyuan Yi, Yongsheng Lin, Liying Zhang, Kit-lun Yick