Assessing the Accuracy of Georeferenced Point Clouds Produced via Multi-View Stereopsis from Unmanned Aerial Vehicle (UAV) Imagery
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Abstract
Sensor miniaturisation, improved battery technology and the availability of low-cost yet advanced Unmanned Aerial Vehicles (UAV) have provided new opportunities for environmental remote sensing. The UAV provides a platform for close-range aerial photography. Detailed imagery captured from micro-UAV can produce dense point clouds using multi-view stereopsis (MVS) techniques combining photogrammetry and computer vision. This study applies MVS techniques to imagery acquired from a multi-rotor micro-UAV of a natural coastal site in southeastern Tasmania, Australia. A very dense point cloud ( < 1–3 cm point spacing) is produced in an arbitrary coordinate system using full resolution imagery, whereas other…
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Authors
2Topics & keywords
Topics
Keywords
- Georeference
- Point cloud
- Remote sensing
- Computer vision
- Stereopsis
- Computer science
- Artificial intelligence
- Point (geometry)
UN Sustainable Development Goals
- Life below water
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