Intelligent Point Cloud Processing, Sensing and Understanding

ISBN 10: 3725802416 / ISBN 13: 9783725802418

Published by MDPI AG, 2024

About this Item

nach der Bestellung gedruckt Neuware - Printed after ordering - Point clouds are deemed to be one of the foundational pillars in representing the 3D digital world, despite irregular topologies among discrete points. Recently, advancements in sensor technologies that acquire point cloud data for flexible and scalable geometric representation have paved the way for the development of new ideas, methodologies, and solutions in countless remote sensing applications. State-of-the-art sensors are capable of capturing and describing objects in a scene by using dense point clouds from various platforms (satellites, aerial, UAVs, vehicle-borne, backpacks, handheld, and static terrestrial), perspectives (nadir, oblique, and side view), spectra (multispectral), and granularity (point density and completeness). Meanwhile, the ever-expanding application areas of point cloud processing have already covered not only conventional domains in geospatial analysis but also manufacturing, civil engineering, construction, transportation, ecology, forestry, mechanical engineering, etc. Readers can learn about the latest innovative technologies for generating, processing, and analyzing point cloud data from these contributions, which helps to understand the challenges faced by point cloud data and develop new 3D applications.

Seller Inventory # 9783725802418

Bibliographic Details

• Title: Intelligent Point Cloud Processing, Sensing and Understanding
• Publisher: MDPI AG
• Publication Date: 2024
• Language: English
• ISBN 10: 3725802416
• ISBN 13: 9783725802418
• Binding: Buch
• Condition: Neu
• Dimensions: 250W x 175H x 18D millimeters 250 millimeters width by 175 millimeters height by 18 millimeters depth
• Weight: 720 grams

About this title

Synopsis

Point clouds are deemed to be one of the foundational pillars in representing the 3D digital world, despite irregular topologies among discrete points. Recently, advancements in sensor technologies that acquire point cloud data for flexible and scalable geometric representation have paved the way for the development of new ideas, methodologies, and solutions in countless remote sensing applications. State-of-the-art sensors are capable of capturing and describing objects in a scene by using dense point clouds from various platforms (satellites, aerial, UAVs, vehicle-borne, backpacks, handheld, and static terrestrial), perspectives (nadir, oblique, and side view), spectra (multispectral), and granularity (point density and completeness). Meanwhile, the ever-expanding application areas of point cloud processing have already covered not only conventional domains in geospatial analysis but also manufacturing, civil engineering, construction, transportation, ecology, forestry, mechanical engineering, etc. Readers can learn about the latest innovative technologies for generating, processing, and analyzing point cloud data from these contributions, which helps to understand the challenges faced by point cloud data and develop new 3D applications.