Martin Weinmann

Reconstruction and Analysis of 3D Scenes

From Irregularly Distributed 3D Points to Object Classes

• Gebundenes Buch

Produktbeschreibung

This
unique work presents a detailed review of the processing and analysis of 3D
point clouds. A fully automated framework is introduced, incorporating each aspect of a typical end-to-end
processing workflow, from raw 3D point cloud data to semantic objects in the
scene. 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. This unique work

Produktdetails

• Verlag: Springer / Springer International Publishing / Springer, Berlin
• Artikelnr. des Verlages: 978-3-319-29244-1
• 1st ed. 2016
• Seitenzahl: 256
• Erscheinungstermin: 31. März 2016
• Englisch
• Abmessung: 241mm x 160mm x 19mm
• Gewicht: 505g
• ISBN-13: 9783319292441
• ISBN-10: 3319292447
• Artikelnr.: 44326888

Inhaltsangabe

Introduction.- 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.

Rezensionen

"The book ... is complete summary for understanding the reconstruction of 3D scenes through the use of point clouds. ... The 'book describes the theoretical background, and compares the performance of the proposed approaches to that of current state-of-the- art techniques.' This book is highly useful to those unfamiliar with laser scanner data gathering including Lidar and would serve as a good first choice to educators teaching about these technologies and processing applications." (Jeff Thurston, 3D Visualization World Magazine, 3dvisworld.com, October, 2016)