By Martin Weinmann
This detailed paintings offers an in depth assessment of the processing and research of 3D element clouds. an absolutely computerized framework is brought, incorporating each one point of a customary end-to-end processing workflow, from uncooked 3D element cloud facts to semantic gadgets within the scene. for every of those elements, the booklet describes the theoretical heritage, and compares the functionality of the proposed techniques to that of present cutting-edge options. issues and contours: stories options for the purchase of 3D element cloud facts and for element caliber review; explains the elemental techniques for extracting good points from 2nd imagery and 3D aspect cloud facts; proposes an unique method of keypoint-based element cloud registration; discusses the enrichment of 3D element clouds by way of additional info obtained with a thermal digital camera, and describes a brand new technique for thermal 3D mapping; provides a unique framework for 3D scene analysis.
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Additional resources for Reconstruction and Analysis of 3D Scenes: From Irregularly Distributed 3D Points to Object Classes
ISPRS Technical Commission III Symposium. ISPRS Annals of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol. II-3, pp. 9–16. • A. C. Braun, M. Weinmann, S. Keller, R. Müller, P. Reinartz and S. Hinz (2015): The EnMAP contest: developing and comparing classification approaches for the Environmental Mapping and Analysis Programme—Dataset and first results. In: C. Mallet, N. Paparoditis, I. Dowman, S. -M. Raimond, G. Sithole, G. Rabatel, F. Rottensteiner, X. Briottet, S. Christophe, A.
While an intensity-based filtering of raw 3D point cloud data is straightforward, easy-to-implement, and quite efficient,5 such considerations do not account for edge effects where noisy range measurements are likely to occur although the respective intensity values might be reasonable. Hence, we focus on two novel strategies which are based on the geometric measures of (i) range reliability and (ii) local planarity in order to quantify the quality of a range measurement. 3 Filtering Based on Range Reliability The first of our proposed measures to quantify the reliability of a range measurement directly addresses the fact that—instead of considering a laser beam as a ray with no physical dimensions—it is inevitable that a laser beam has certain physical dimensions which, in turn, influences the laser beam propagation.
Hinz S, Weinmann M, Runge P, Jutzi B (2011) Potentials of image based active ranging to capture dynamic scenes. Int Arch Photogramm Remote Sens Spat Inf Sci XXXVIII-4/W19:143– 147 3. Paparoditis N, Papelard J-P, Cannelle B, Devaux A, Soheilian B, David N, Houzay E (2012) Stereopolis II: a multi-purpose and multi-sensor 3D mobile mapping system for street visualisation and 3D metrology. Revue Française de Photogrammétrie et de Télédétection 200:69–79 4. Rusu RB, Cousins S (2011) 3D is here: Point Cloud Library (PCL).
Reconstruction and Analysis of 3D Scenes: From Irregularly Distributed 3D Points to Object Classes by Martin Weinmann