立体摄像机鲁棒自动标定技术

Hamdi Boukamcha, Mohamed Atri, F. Smach
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引用次数: 2

摘要

立体视觉摄像机内外参数的标定是计算机视觉领域一个著名的研究课题。通常,为了获得准确的3D效果,相机也需要手动精确校准。提出了一种无需用户干预的立体摄像机鲁棒自动标定方法。有几种校准方法和技术已经被证明,在这项工作中,我们利用几何约束,即极几何。我们特别关注使用7种技术进行特征提取(SURF, BRISK, FAST, FREAK, MinEigen, MSERF, SIFT),并尝试使用各种匹配技术(SSD, SAD, Hamming)建立立体图像中提取点之间的对应关系。然后,我们利用基本矩阵通过选择完美的八点算法(Norm8Point, lmed, RANSAC, MSAC, LTS)来估计极线。进行了大量的实验,通过比较和选择各个阶段的最佳工艺,取得了很好的效果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Robust auto calibration technique for stereo camera
Calibration of the internal and external parameters of a stereo vision camera is a well-known research problem in the computer vision. Usually, to get accurate 3D results the camera should be manually calibrate accurately as well. This paper proposes a robust approach to Auto Calibration stereo camera Without intervention of the user. There are several methods and techniques of calibration that have been proven, in this work we exploiting the geometric constraint, namely, the epipolar geometry. We specifically focuses to use 7 techniques for Features Extraction (SURF, BRISK, FAST, FREAK, MinEigen, MSERF, SIFT), however tries to establish the correspondences between points extracted in stereo images with Various Matching Techniques (SSD, SAD, Hamming). Then we exploits the Fundamental Matrix to estimate the epipolar Line by choosing the perfect Eight-point algorithms (Norm8Point, LMedS, RANSAC, MSAC, LTS). A large number of experiments have been carried out, and very good results have been obtained by Comparison & choice the perfect technique in every stage.
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