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Euclidean 3D reconstruction from image sequences with variable focal lengths

机译:欧几里德3D从具有可变焦距的图像序列重建

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One of the main problems to obtain a Euclidean 3D reconstruction from multiple views is the calibration of the camera. Explicit calibration is not always practical and has to be repeated regularly. Sometimes it is even impossible (i.e. for pictures taken by an unknown camera of an undnown scene). The second possibility is to do auto-calibration. Here the rigidity of the scene is used to obtain constraints on the camera parameters. Existing approaches of this second strand impose that the camera parameters stay exactly the same between different views. This can be very limiting since it excludes changing the focal length to zoom or focus. The paper describes a reconstruction method that allows to vary the focal length. Instead of using one camera one can also use a stereo rig following similar principles, and in which case also reconstruction from a moving rig becomes possible even for pure translation. Synthetic data were used to see how resistant the algorithm is to noise. The results are satisfactory. Also results for a real scene were convincing.
机译:从多视图获得欧几里德3D重建的主要问题之一是相机的校准。显式校准并不总是实用的,必须经常重复。有时它甚至是不可能的(即,对于由未经证明的场景的未知相机拍摄的照片)。第二种可能性是进行自动校准。这里使用场景的刚性来获得相机参数的约束。该第二股的现有方法施加了相机参数在不同视图之间保持完全相同。这可能非常有限,因为它排除了改变焦距以缩放或焦点。本文描述了一种允许改变焦距的重建方法。代替使用一个相机也可以使用以下类似原理的立体声钻机,并且在这种情况下,即使对于纯平移也可能从移动装置重建。合成数据用于了解算法如何噪音。结果令人满意。还有一个真正的现场令人信服的结果。

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