By Martin Weinmann
This particular paintings offers a close evaluate of the processing and research of 3D element clouds. a completely computerized framework is brought, incorporating every one point of a standard end-to-end processing workflow, from uncooked 3D aspect cloud info 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 thoughts. subject matters and lines: reports innovations for the purchase of 3D element cloud facts and for element caliber overview; explains the basic innovations for extracting positive factors from 2nd imagery and 3D element cloud facts; proposes an unique method of keypoint-based element cloud registration; discusses the enrichment of 3D element clouds by means of additional info received with a thermal digicam, and describes a brand new strategy for thermal 3D mapping; offers a unique framework for 3D scene analysis.
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Additional info for Reconstruction and Analysis of 3D Scenes: From Irregularly Distributed 3D Points to Object Classes
Weinmann M, Jutzi B, Mallet C (2013) Feature relevance assessment for the semantic interpretation of 3D point cloud data. ISPRS Ann Photogramm Remote Sens Spat Inf Sci II-5/W2:313– 318 17. Weinmann M, Jutzi B, Mallet C (2014) Describing Paris: automated 3D scene analysis via distinctive low-level geometric features. In: Proceedings of the IQmulus workshop on processing large geospatial data, pp 1–8 18. Weinmann M, Jutzi B, Mallet C (2014): Semantic 3D scene interpretation: a framework combining optimal neighborhood size selection with relevant features.
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. Çöltekin, and G. ), ISPRS Geospatial Week 2015. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol.
Accounting for both intensity and range information, the combination of removing points with low values in the intensity image as well as points at edges in the range image has been proposed in order to obtain an adequate 3D representation of a scene . Furthermore, it should be taken into account that the scanning geometry with respect to the incidence angle may have a significant influence on the accuracy of a range measurement which becomes visible by an increase in measurement noise with increasing incidence angles .