Pairwise 3D point cloud registration derived from Terrestrial Laser Scanner (TLS) in static mode is an essential task to produce locally consistent 3D point clouds. In this work, the contributions are twofold. First, a non-iterative scheme by merging the SIFT (Scale Invariant Feature Transform) 3D algorithm and the PFH (Point Feature Histograms) algorithm to find initial approximation of the transformation parameters is proposed. Then, a correspondence model based on a new variant of the ICP (Iterative Closest Point) algorithm to refine the transformation parameters is also proposed. To evaluate the local consistency of the pairwise 3D point cloud registration is used a point-to-distance approach. Experiments were performed using seven pairs of 3D point clouds into an urban area. The results obtained showed that the method achieves point-to-plane RMSE (Root of the Mean Square Error) mean values in the order of 2 centimeters.


    Access

    Download


    Export, share and cite



    Title :

    A New Variant of the ICP Algorithm for Pairwise 3D Point Cloud Registration



    Publication date :

    2022-01-01


    Remarks:

    American Academic Scientific Research Journal for Engineering, Technology, and Sciences; Vol 85 No 1 (2022); 71-88 ; 2313-4402 ; 2313-4410


    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



    Classification :

    DDC:    629




    Global Optimisation for Point Cloud Registration with the Bees Algorithm

    Lan, Feiying / Castellani, Marco / Wang, Yongjing et al. | Springer Verlag | 2022


    A Novel Representation and Feature Matching Algorithm for Automatic Pairwise Registration of Range Images

    Mian, A. S. / Bennamoun, M. / Owens, R. A. | British Library Online Contents | 2006


    A Novel 3D Point Cloud Registration Algorithm Based on Hybrid Line Features

    You, Danlei / Zhang, Songyi / Chen, Shitao et al. | IEEE | 2021


    HD2Reg: Hierarchical Descriptors and Detectors for Point Cloud Registration

    Tang, Canhui / Li, Yiheng / Du, Shaoyi et al. | IEEE | 2023