Conference Agenda

To meet the growing demand for 3D digital map applications and to better understand the multi-level spatial structure of cities, some cities have implemented citywide 3D digital map programs. In 3D digital map production, vehicle-mounted mobile surveying is a key component. Drawing with a practical project, this paper proposes a technical scheme for road data acquisition and processing based on the SSW VMMS (Vehicle-mounted Mobile Mapping System). Through integrated processing steps, including combined navigation solution, point cloud correction, image coordinate calculation, image deblurring, point cloud coloring, point cloud denoising, and Orbit GT data preparation, the rapid production of colored point cloud data with georeferenced coordinates, 360° panoramic image data, and individual image data is achieved. A technical scheme suitable for 3D digital map production along urban roads was developed and validated. The results produced by this scheme have passed inspection and acceptance, and were released to the public free of charge as the first batch of visualized 3D map data on the Common Spatial Data Infrastructure Portal (portal.csdi.gov.hk), receiving widespread attention and positive recognition from various sectors of society. This scheme not only promotes the broader application of the SSW VMMS but also provides effective reference for similar urban vehicle-mounted mobile mapping projects.

We present an automatic algorithm for graph-based road network extraction from remote sensing images. While existing works mostly focus on improving accuracy, we address the problem of the geometric quality of the output graphs. The state-of-the-art methods largely overlook this aspect by generating graphs without strong geometric guarantees, regularity preservation and low-complexity, which, ultimately, reduces their impact in many application scenarios. Our algorithm relies upon foundation models that analyze road networks with pixel-based representations, as well as geometric algorithms and data structures in charge of connecting geometric primitives into planar graphs. This hybrid strategy allows us to strongly enforce the geometric quality of the output graphs while bringing a high level of generalization. We show the potential of our algorithm and its advantages over existing methods on two datasets commonly-used in the field using both the conventional accuracy metrics and new metrics introduced to measure the geometric quality of the output graphs.

High-resolution monitoring of road infrastructure is essential for the early detection of geomorphological instabilities such as landslides and erosion. This study evaluates the performance of handled MMS under different vehicle-mounted configurations: a 2-meter survey pole versus a suction-cup mount, and varying acquisition speeds (10 and 20 km/h). Furthermore, a GNSS-denied scenario was simulated to test the robustness of SLAM-based processing. Initial results revealed significant geometric discrepancies (double-points artifacts and drift), particularly in the SLAM-only and high-speed datasets. To address this, an automated segment-based refinement workflow was developed using a ICP algorithm. The refinement successfully reduced the standard deviation to the level of the point cloud´s mean point spacing (5 cm). Comparative multitemporal analysis against UAV-LiDAR reference data confirms that the proposed refinement renders even SLAM-processed data viable for detecting centimetric terrain displacements. The findings demonstrate that while suction-cup mounting at 10 km/h is optimal, algorithmic refinement allows for reliable road slopes monitoring and change detection across all tested configurations

Underground utilities such as water pipelines and sewers are critical for urban systems, yet their management is challenging due to limited accessibility and uncertain positional data. Current inspection practices rely on robotic crawlers equipped with CCTV cameras or man-entry inspections, enabling visual documentation of structural conditions but lacking accurate georeferencing of internal points. Advanced solutions relying on panoramic imaging and IMUs offer partial 3D measurements and trajectory estimation, though accuracy remains limited by drift and environmental variability.

This study investigates the feasibility of multi-camera photogrammetry for mapping pipelines and confined underground environments and improving positional accuracy. Preliminary experiments were conducted using the Atom-Ant3D system on two test sets: (i) five pipelines of varying materials (concrete, PVC, fiberglass) and diameters (60–110 cm); and (ii) a 1.3 km water-distribution tunnel (~2 m diameter) prepared with 28 fixed targets measured via total station for accuracy evaluation. Data were acquired using robotic and handheld configurations and processed through two workflows: Structure-from-Motion (SfM) and multi-view V-SLAM.

Accuracy assessment focused on the tunnel test, comparing unconstrained and constrained trajectories against a reference solution. Results provide insights into the potential of photogrammetric approaches for precise pipeline reconstruction and georeferencing, supporting improved subsurface utility management and planning.

3D multi-view, multi-object tracking (3D MV-MOT) makes use of multiple cameras to reduce the number of missed detections and to mitigate occlusions. Most current 3D MV-MOT methods suffer from information loss when associating 3D locations with 2D image features via a 3D-to-2D projection, as they use a discrete grid in 3D and sample image features only at the projected centers of each grid cell. Thus, all other feature information is lost. An additional information loss commonly arises during cross-view aggregation when applying max or average pooling: these methods either overemphasize a single view or treat conflicting views, that depict different entities, e.g., due to occlusions, equally.

In this work, we introduce two novel modules for 3D MV-MOT, employed to pedestrian tracking, that target these limitations:

(i) VoxROI aggregates all image features that fall within the bounding box around a voxel's projection into each respective image, instead of only sampling features at the projected voxel center.

(ii) SimFuse aggregates per-view voxel features into one coherent feature representation per voxel, using similarity weights computed from re-identification (Re-ID) features.

Subsequently, they are used to measure cross-view identity similarity. Views with higher Re-ID feature similarity receive larger weights, while inconsistent views are suppressed.

Experimental results on the WildTrack dataset confirm our method's effectiveness for multi-view pedestrian detection and tracking, reaching, and in particular in cross-view scenarios improving, the general state-of-the-art. The approach maintains strong performance across different camera configurations, demonstrating its generalization capability when training and testing on different camera setups.

With the rapid growth of urban low-altitude applications, traditional airspace management approaches based on simple altitude limits and static no-fly zones can no longer meet the demands of high-density and highly dynamic operations. To address this issue, this study proposes a fine-grained gridding method for urban low-altitude airspace with dynamic event response and vertical flight corridor constraints. First, a unified three-dimensional grid model is constructed on the basis of an urban 3D digital twin platform, and the grid scale and update cycle are determined by jointly considering clearance requirements and safety separation. Second, a method for injecting static and dynamic attributes is established to achieve the unified representation and continuous updating of terrain, buildings, no-fly and restricted zones, wind fields, temporary restrictions, as well as occupancy and release information within the grid. Third, fixed-geometry and dynamically open vertical flight corridors are designed to support controlled cross-layer flight transitions and reduce the risk of vertical conflict propagation. An experimental system is developed using a typical high-density urban area in Yuehai Subdistrict, Nanshan District, Shenzhen, as the case study. The results show that the proposed method can achieve stable spatial discretization, accurate attribute loading and updating, and clear organization of cross-layer flight. The proposed method provides a unified technical framework for low-altitude airspace representation, state management, and operational governance in complex urban environments.