000			03591nam a22005295i 4500
001			978-3-319-29246-5
003			DE-He213
005			20200421112548.0
007			cr nn 008mamaa
008			160317s2016 gw | s |||| 0|eng d
020			_a9783319292465 _9978-3-319-29246-5
024	7		_a10.1007/978-3-319-29246-5 _2doi
050		4	_aTA1637-1638
050		4	_aTA1634
072		7	_aUYT _2bicssc
072		7	_aUYQV _2bicssc
072		7	_aCOM012000 _2bisacsh
072		7	_aCOM016000 _2bisacsh
082	0	4	_a006.6 _223
082	0	4	_a006.37 _223
100	1		_aWeinmann, Martin. _eauthor.
245	1	0	_aReconstruction and Analysis of 3D Scenes _h[electronic resource] : _bFrom Irregularly Distributed 3D Points to Object Classes / _cby Martin Weinmann.
250			_a1st ed. 2016.
264		1	_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2016.
300			_aXXII, 233 p. 81 illus., 69 illus. in color. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
505	0		_aIntroduction -- Preliminaries of 3D Point Cloud Processing -- A Brief Survey on 2D and 3D Feature Extraction -- Point Cloud Registration -- Co-Registration of 2D Imagery and 3D Point Cloud Data -- 3D Scene Analysis -- Conclusions and Future Work.
520			_aThis unique text/reference presents a detailed review of the processing and analysis of 3D point clouds. A fully automated framework is introduced for the complete processing workflow, incorporating the filtering of noisy data, the extraction of appropriate features, the alignment of 3D point clouds in a common coordinate frame, the enrichment of 3D point cloud data with other types of information, and the semantic interpretation of 3D point clouds. For each of these components, the book describes the theoretical background, and compares the performance of the proposed approaches to that of current state-of-the-art techniques. Topics and features: Reviews techniques for the acquisition of 3D point cloud data and for point quality assessment Explains the fundamental concepts for extracting features from 2D imagery and 3D point cloud data Proposes an original approach to keypoint-based point cloud registration Discusses the enrichment of 3D point clouds by additional information acquired with a thermal camera, and describes a new method for thermal 3D mapping Presents a novel framework for 3D scene analysis, addressing neighborhood selection, feature extraction, feature selection, and classification Covers each aspect of a typical end-to-end processing workflow, from raw 3D point cloud data to semantic objects in the scene This clearly-structured and accessible work will be of great interest to a broad audience, from students at undergraduate or graduate level, to lecturers, practitioners and researchers in photogrammetry, remote sensing, computer vision and robotics.
650		0	_aComputer science.
650		0	_aArtificial intelligence.
650		0	_aImage processing.
650		0	_aRemote sensing.
650	1	4	_aComputer Science.
650	2	4	_aImage Processing and Computer Vision.
650	2	4	_aRemote Sensing/Photogrammetry.
650	2	4	_aArtificial Intelligence (incl. Robotics).
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9783319292441
856	4	0	_uhttp://dx.doi.org/10.1007/978-3-319-29246-5
912			_aZDB-2-SCS
942			_cEBK
999			_c58678 _d58678