At present, g2o (general graph optimization) is the main method of reducing the accumulated errors of point cloud registration, an important step of 3D scene reconstruction. However, the huge amount of point cloud data produced in the application process leads to the failure of meeting real -time request. Since cuboid is the most common indoor geometric structure of buildings , this paper presents an optimization method using planar features of point cloud. We rapidly extract the planes from point cloud and modify the transfer matrix of pair point c louds based on planar rotation. Results show that, by regulating down sampling threshold, the treatment time of each frame of point cloud data can be approximately shortened to 1.8486s in comparison of 3.08683s by g2o. Besides, the algorism ensures the matching effect and thus has strong robustness.
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