Abstract
An approach for the co-registration of Digital Surface Models (DSMs) derived from Unmanned Aerial Vehicles (UAVs) and Terrestrial Laser Scanners (TLS) is proposed. Specifically, a wavelet-based feature descriptor for matching surface keypoints on the 2.5D DSMs is developed. DSMs are useful in wide-scope of various applications such as 3D building modelling and reconstruction, cultural heritage, urban and environmental planning, aircraft navigation/path routing, accident and crime scene reconstruction, mining as well as, topographic map revision and change detection. For these listed applications, it is not uncommon that there will be a need for automatically aligning multi-temporal DSMs which may have been acquired from multiple sensors, with different specifications over a period of time, and may have various overlaps. Terrestrial laser scanners usually capture urban facades in an accurate manner; however this is not the case for building roof structures. On the other hand, vertical photography from UAVs can capture the roofs. Therefore, the automatic fusion of UAV and laser-scanning based DSMs is addressed here as it serves various geospatial applications.
Highlights
Vertical Unmanned Aerial Vehicles (UAVs) imagery enables us to capture roof details of buildings and other absent structure data which terrestrial laser scanners (TLS) may not be able to capture
Fusion of UAV and TLS data can be used in a variety of geospatial applications such as cultural heritage, urban and environmental planning, aircraft navigation/path routing, accident and crime scene reconstruction, mining, as well as, topographic map revision and change detection
We propose an approach to automatically co-register UAV and TLS Digital Surface Models (DSMs)
Summary
Vertical UAV imagery enables us to capture roof details of buildings and other absent structure data which terrestrial laser scanners (TLS) may not be able to capture. For aligning a DSM pair, corresponding features and the mathematical transformation to map the „source‟ DSM to „target‟ DSM must be established. We propose an approach to automatically co-register UAV and TLS DSMs. The problem of co-registering a pair of DSMs (i.e., a 'source' and 'target' DSM) depends on the type of unknown transformation parameters which has to be retrieved. The problem of co-registering a pair of DSMs (i.e., a 'source' and 'target' DSM) depends on the type of unknown transformation parameters which has to be retrieved If both DSM are of the same scale but are displaced by unknown rotation and translation, global alignment can be achieved by shifting centroids and applying a principal component analysis-based orientation. A feature matching approach is used for this purpose (Fig. 1)
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