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What Can We Learn About The Scene Structure From Three Orthogonal Vanishing Points In Images

机译:我们可以从图像中的三个正交消失点了解场景结构

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The problem of 3D Euclidean reconstruction of structured scenes from uncalibrated images based on the property of vanishing points is studied in this paper.Under the assumption of three-parameter-camera model with varying parameters,we prove that under an arbitrary preassigned world coordinate system,the camera projection matrix of an image can be uniquely determined from three mutually orthogonal vanishing points obtained from the image.When multiple images of the object are present,it is proved that the global consistent projection matrices can be recovered if an arbitrary reference point in space is observed across the views.For the scenario with multiple objects,we may reconstruct each object individually by the proposed method,then register and align them together via the technique of visual metrology so as to obtain the 3D structure of the entire scene.Compared with previous stereovision techniques,the proposed method avoids the bottleneck problem of feature matching and is easy to implement,therefore,more accurate,robust and realistic results are expected.Extensive experiments on synthetic and real world images validate the effectiveness of the proposed method.
机译:本文研究了基于消失点性质的非标定图像3D欧氏重建问题。在参数可变的三参数相机模型的假设下,证明了在任意预定的世界坐标系下,图像的相机投影矩阵可以从图像中获得的三个相互正交的消失点唯一地确定。当存在物体的多个图像时,证明了如果在空间中有任意参考点,则可以恢复全局一致的投影矩阵。对于具有多个对象的场景,我们可以通过提出的方法分别重构每个对象,然后通过视觉计量技术将它们注册并对齐在一起,以获得整个场景的3D结构。该方法克服了以往的立体视觉技术,避免了特征匹配的瓶颈问题,操作简便。因此,期望能够实现更加准确,稳健和逼真的结果。对合成和真实世界图像进行的大量实验验证了该方法的有效性。

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