Abstract
The registration of pairs of Terrestrial Laser Scanning data (TLS) is an integral precursor to 3D data analysis. Of specific interest in this research work is the class of approaches that is considered to be fine registration and which does not require any targets or tie points. This paper presents a pairwise fine registration approach called P2P that is formulated using the General Least Squares adjustment model. Given some initial registration parameters, the proposed P2P approach utilizes the scanned points and estimated planar features of both scans, along with their stochastic properties. These quantities are used to determine the optimum registration parameters in the least squares sense. The proposed P2P approach was tested on both simulated and real TLS data, and experimental results showed it to be four times more accurate than the registration approach of Chen and Medioni (1991).
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