LEADER 04487nam 2201165z- 450 001 9910595072603321 005 20220916 035 $a(CKB)5680000000080800 035 $a(oapen)https://directory.doabooks.org/handle/20.500.12854/92145 035 $a(oapen)doab92145 035 $a(EXLCZ)995680000000080800 100 $a20202209d2022 |y 0 101 0 $aeng 135 $aurmn|---annan 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 00$aTechniques and Applications of UAV-Based Photogrammetric 3D Mapping 210 $aBasel$d2022 215 $a1 online resource (294 p.) 311 08$a3-0365-5067-4 311 08$a3-0365-5068-2 330 $aThe 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. 606 $aHistory of engineering & technology$2bicssc 606 $aTechnology: general issues$2bicssc 610 $a3D point cloud 610 $a3D reconstruction 610 $aaerial triangulation 610 $aaffine invariant feature 610 $aaggregate semantic information 610 $aairborne LiDAR 610 $aBrown model 610 $abuilding extraction 610 $abuilding fac?ade 610 $abuilding footprint 610 $abuilding height 610 $acamera self-calibration 610 $acoal mine 610 $acompound building reconstruction 610 $aconvolutional neural network 610 $acoplanar extraction 610 $acycle consistency inference 610 $adeep convolutional neural network 610 $adeep learning 610 $adeformation detection 610 $adense shortcut 610 $adepth estimation 610 $adepth map fusion 610 $adetail preserving 610 $adigital photogrammetry 610 $adigital subsidence model 610 $aeffective feature distillation 610 $afeature pyramid 610 $ageometric topology 610 $aGF-7 image 610 $ahigh-frequency loss 610 $ahigh-resolution remote sensing images 610 $ahomography matrix 610 $aimage matching 610 $aindoor scene 610 $aleast square fitting 610 $aLiDAR 610 $alightweight image super-resolution 610 $amatch pair 610 $amulti-view 610 $amulti-view reconstruction 610 $amultiscale features 610 $an/a 610 $aPatchMatch 610 $aphotogrammetric mesh model 610 $apoint cloud 610 $apoint clouds 610 $apolynomial model 610 $apower lines 610 $ared-black propagation 610 $arepetitive structure 610 $asemantic decomposition 610 $asemantic segmentation 610 $asingle image super-resolution 610 $aspatial eight-quadrant kernel convolution 610 $astructure from motion 610 $asurface meshing 610 $asurface subsidence 610 $atexture mapping 610 $aU-shaped residual network 610 $aUAV inspection 610 $avery short baseline 610 $awide-baseline stereo image 615 7$aHistory of engineering & technology 615 7$aTechnology: general issues 700 $aJiang$b Wanshou$4edt$01332328 702 $aJiang$b San$4edt 702 $aXiao$b Xiongwu$4edt 702 $aJiang$b Wanshou$4oth 702 $aJiang$b San$4oth 702 $aXiao$b Xiongwu$4oth 906 $aBOOK 912 $a9910595072603321 996 $aTechniques and Applications of UAV-Based Photogrammetric 3D Mapping$93040839 997 $aUNINA