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Camera self-calibration having the varying parameters and based on homography of the plane at infinity

机译:具有可变参数并基于无穷远平面的单应性的相机自校准

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In this approach, we will process a self-calibration problem of camera characterized by varying parameters. Our approach is based on estimating of homography of the plane at infinity and depths of interest points. This estimation is made from resolution of nonlinear equation system that is formulated from the projection of some points of the scene in the planes of different images. The relationships established between the homography of the plane at infinity and matches, between images, and those established between points of the 3D scene and their projections, in image planes, allow formulating the second nonlinear equations. This system is minimized by using the Levenberg-Marquardt algorithm to estimate the intrinsic parameters of used camera. This approach has several strong points: i) The use of any cameras (having varying parameters), ii) The use of any scenes (3D) and iii) the use of a minimum number of images (two images only). Experiments and simulations show the performance of this approach in terms of stability, accuracy and convergence.
机译:在这种方法中,我们将处理以变化的参数为特征的摄像机的自校准问题。我们的方法基于在无穷大和兴趣点深度处平面的单应性的估计。该估计是根据非线性方程系统的分辨率进行的,该方程是根据场景中某些点在不同图像平面中的投影得出的。在无穷远处的平面单应性与图像之间的匹配之间建立的关系,以及在图像平面中在3D场景的点与它们的投影之间建立的那些关系允许公式化第二个非线性方程式。通过使用Levenberg-Marquardt算法来估计使用过的相机的内在参数,可以最小化该系统。这种方法有几个优点:i)使用任何相机(参数各不相同),ii)使用任何场景(3D)和iii)使用最少数量的图像(仅两个图像)。实验和仿真显示了这种方法在稳定性,准确性和收敛性方面的性能。

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