Façade image recognition under complex illumination conditions is crucial for various applications, including urban three-dimensional modeling and building identification. Existing methods relying solely on Red-Green-Blue (RGB) images are prone to …
The absence of detailed façade elements in photogrammetric building mesh models falls short for complex applications. These models often present irregular surfaces, significant geometric noise, and subpar texture quality, complicating façade parsing. …
The accurate representation of 3D building models in urban environments is significantly hindered by challenges such as texture occlusion, blurring, and missing details, which are difficult to mitigate through standard photogrammetric texture mapping …
Most urban applications necessitate building footprints in the form of concise vector graphics with sharp boundaries rather than pixel-wise raster images. This need contrasts with the majority of existing methods, which typically generate …
Mobile mapping systems, which are equipped with a laser scanner, panoramic camera, and inertial navigation system, can flexibly and efficiently obtain precision point clouds. However, these systems require re-installation for each mission, which …
Automatic and periodic recompiling of building databases with up-to-date high-resolution images has become a critical requirement for rapidly developing urban environments. However, the architecture of most existing approaches for change extraction …
Point-based and voxel-based methods can learn the local features of point clouds. However, although point-based methods are geometrically precise, the discrete nature of point clouds negatively affects feature learning performance. Moreover, although …
Compared with the existing modes of LiDAR, single-photon LiDAR (SPL) can acquire terrain data more efficiently. However, influenced by the photon-sensitive detectors, the collected point cloud data contain a large number of noisy points. Most of the …
Many methods have been proposed to extract line segment (LS) correspondences for images with viewpoint variations. However, the matching performance on images with viewpoint variations is still limited due to the influence of discontinuous parallax …
Due to the irregularity and complexity of ground and non-ground objects, filtering non-ground data from airborne LiDAR point clouds to create Digital Elevation Models (DEMs) remains a longstanding and unresolved challenge. Recent advancements in deep …