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Robust auto calibration technique for stereo camera

机译:立体相机的鲁棒自动校准技术

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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.
机译:立体视觉摄像头的内部和外部参数的校准是计算机视觉中的知名研究问题。通常,为了获得准确的3D结果,也应该准确地手动校准相机。本文提出了一种在没有用户干预的情况下自动校准立体声相机的强大方法。在这项工作中,有几种方法和校准技术,在这项工作中,我们利用几何约束,即末极几何形状。我们专注于使用7种技术提取(冲浪,快速,快速,怪物,雷训,MSERF,SIFT),但试图建立在具有各种匹配技术中提取的立体图像中提取的点之间的对应关系(SSD,SAD,HAMPing)。然后我们通过选择完美的八点算法(NORM8POINT,LMEDS,RANSAC,MSAC,LTS)来利用基本矩阵来估计ePipolar线路。已经进行了大量实验,并且通过比较和选择每个阶段的完美技术获得了非常好的结果。

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