Recent increased popularity of RGB-D capable sensors in robotics has resulted in a surge of related RGBD registration methods. This paper presents several RGB-D registration algorithms based on combinations between local visual feature and geometric registration. Fast and accurate transformation refinement is obtained by using a recently proposed geometric registration algorithm, based on the Three-Dimensional Normal Distributions Transform (3D-NDT). Results obtained on standard data sets have demonstrated mean translational errors on the order of 1 cm and rotational errors bellow 1 degree, at frame processing rates of about 15 Hz.
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