This 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.