Automatic dimension inspection of industrial parts based on 3D point cloud
暂无分享,去创建一个
[1] Robert C. Bolles,et al. Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography , 1981, CACM.
[2] Jie Sun,et al. Intelligent optimization of seam-line finding for orthophoto mosaicking with LiDAR point clouds , 2011, Journal of Zhejiang University SCIENCE C.
[3] Vladlen Koltun,et al. Fast Global Registration , 2016, ECCV.
[4] Hong Bin Chen,et al. Study of Large Scale Measurement Method Based on Leapfrog Principle , 2011 .
[5] Hongzhi Jiang,et al. High dynamic range fringe acquisition: A novel 3-D scanning technique for high-reflective surfaces , 2012 .
[6] Sven Behnke,et al. Registration with the Point Cloud Library: A Modular Framework for Aligning in 3-D , 2015, IEEE Robotics & Automation Magazine.
[7] Derek D. Lichti,et al. Pre‐processing procedures for raw point clouds from terrestrial laser scanners , 2007 .
[8] Jan-Michael Frahm,et al. A Comparative Analysis of RANSAC Techniques Leading to Adaptive Real-Time Random Sample Consensus , 2008, ECCV.
[9] Michael J. Black,et al. On the unification of line processes, outlier rejection, and robust statistics with applications in early vision , 1996, International Journal of Computer Vision.