Techniques and Applications of UAV-Based Photogrammetric 3D Mapping

• Autore: Jiang Wanshou
• Pubblicazione: Basel, 2022
• Descrizione fisica: 1 online resource (294 p.)
• Soggetto topico: History of engineering & technology; Technology: general issues
• Soggetto non controllato: 3D point cloud; 3D reconstruction; aerial triangulation; affine invariant feature; aggregate semantic information; airborne LiDAR; Brown model; building extraction; building façade; building footprint; building height; camera self-calibration; coal mine; compound building reconstruction; convolutional neural network; coplanar extraction; cycle consistency inference; deep convolutional neural network; deep learning; deformation detection; dense shortcut; depth estimation; depth map fusion; detail preserving; digital photogrammetry; digital subsidence model; effective feature distillation; feature pyramid; geometric topology; GF-7 image; high-frequency loss; high-resolution remote sensing images; homography matrix; image matching; indoor scene; least square fitting; LiDAR; lightweight image super-resolution; match pair; multi-view; multi-view reconstruction; multiscale features; n/a; PatchMatch; photogrammetric mesh model; point cloud; point clouds; polynomial model; power lines; red-black propagation; repetitive structure; semantic decomposition; semantic segmentation; single image super-resolution; spatial eight-quadrant kernel convolution; structure from motion; surface meshing; surface subsidence; texture mapping; U-shaped residual network; UAV inspection; very short baseline; wide-baseline stereo image
• Persona (resp. second.): JiangSan; XiaoXiongwu; JiangWanshou
• Sommario/riassunto: The book focuses on the techniques for UAV-based 3D mapping and its applications in varying fields since the explosive development of UAV-based photogrammetric 3D mapping and their wide applications from traditional surveying and mapping to other related fields have been witnessed in photogrammetry and remote sensing. In the last decade, unmanned aerial vehicle (UAV) images have become one of the most important remote sensing data sources for photogrammetric 3D mapping. Besides, the rapid development of recent techniques, e.g., SfM (Structure from Motion) for off-line image orientation, SLAM (Simultaneous Localization and Mapping) for on-line UAV navigation, and the deep learning (DL) embedded 3D reconstruction pipeline, has promoted UAV-based 3D mapping towards the direction of automation and intelligence. It is really worthy to collecting the cutting-edge techniques and reporting their promising applications.
• Titolo autorizzato: Techniques and Applications of UAV-Based Photogrammetric 3D Mapping
• Formato: Materiale a stampa
• Livello bibliografico: Monografia
• Lingua di pubblicazione: Inglese
• Record Nr.: 9910595072603321
• Lo trovi qui: Univ. Federico II