After successful completion of this course, the student should be able to:
- Design survey plans to acquire point clouds of outdoor and indoor environments taking into account the accuracy and point density requirements.
- Evaluate the quality of laser scanning datasets.
- Select and apply the best methods for point cloud segmentation, classification, and object modelling.
- Interpret and analyse point cloud processing results.
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Airborne, terrestrial and mobile laser scanning are modern technologies to acquire and monitor the geometry of the Earth's surface and objects above the surface like buildings, trees, and road infrastructure, and even building interiors. This course provides an overview of the state of the art of these techniques, potential applications as well as methods to extract geo-information from the recorded point clouds.
Topics addressed are:
- Principles of airborne, terrestrial, and mobile laser scanning
- Sensor and point cloud properties
- Point cloud visualisation
- Point cloud segmentation methods: surface growing, RANSAC, Hough transform
- Classification of point clouds: handcrafted features and deep learning
- 3D landscape modelling for digital twins
- Acquisition and modelling of indoor environments
Assessment
Written exam (80%), individual assignment (20%)
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