Abstract-We present a new algorithm for scan registration of colored 3D point data which is an extension to the Normal Distributions Transform (NDT). The probabilistic approach of NDT is extended to a color-aware registration algorithm by modeling the point distributions as Gaussian mixture-models in color space. We discuss different point cloud registration techniques, as well as alternative variants of the proposed algorithm. Results showing improved robustness of the proposed method using real-world data acquired with a mobile robot and a time-of-flight camera are presented.
Huhle et al. REF register scans of 3D point data by extending the standard metric with color information using Gaussian mixture models in a color space.
Registration of colored 3D point clouds with a Kernel-based extension to the normal distributions transform
2008 IEEE International Conference on Robotics and Automation
2008 IEEE International Conference on Robotics and Automation
Computer Science