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"Photogrammetry is the art, science, and technology of obtaining reliable information about physical objects and the environment, through processes of recording, measuring, and interpreting imagery and digital representations of energy patterns derived from non-contact sensor systems.” Colwell (1997) This class explains the fundaments of using Photogrammetry and LiDAR techniques to acquire spatial information. The aim of the course is to provide in-depth knowledge of imaging and LiDAR techniques for acquiring 3D geometric information and further investigating image classification and recognition.

This course treats selected topics of digital photogrammetry: 1. Introduction 2. Fully Automated Image Pose Estimation • Image Feature Extraction • Image Feature Matching • Image Registration 3. Orthoimage Generation 4. Image Classification • Supervised Classification Methods • Unsupervised Classification Methods 5. Image Recognition • Moving Object detection • Object Recognition 6. LiDAR Data Processing • Data Characteristics • LiDAR Platforms • Point Cloud Registration • Point Cloud Classification 7. DEM Extraction from Point Clouds 8. Photorealistic Model Generation (Integration of LiDAR and Imagery)

General performance 20% Assignment 30% Final exam 50%

• Digital Photogrammetry
• LiDAR-grammetry
• Assignment

Digital Photogrammetry, Volume I Toni F. Schenk Publisher TerraScience, 1999 ISBN 0967765315, 9780967765310 Photogrammetric Computer Vision: Statistics, Geometry, Orientation and Reconstruction Wolfgang Förstner, Bernhard P. Wrobel Publisher Springer Cham, 2016 ISBN 978-3-319-11549-8

地點

EB-323

時間

Wed. 13:30 - 15:30

聯絡方式

jtychuang@nycu.edu.tw