Contour-Based Structure from Reflection

Po-Hao Huang, S. Lai
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引用次数: 22

Abstract

In this paper, we propose a novel contour-based algorithm for 3D object reconstruction from a single uncalibrated image acquired under the setting of two plane mirrors. With the epipolar geometry recovered from the image and the properties of mirror reflection, metric reconstruction of an arbitrary rigid object is accomplished without knowing the camera parameters and the mirror poses. For this mirror setup, the epipoles can be estimated from the correspondences between the object and its reflection, which can be established automatically from the tangent lines of their contours. By using the property of mirror reflection as well as the relationship between the mirror plane normal with the epipole and camera intrinsic, we can estimate the camera intrinsic, plane normals and the orientation of virtual cameras. The positions of the virtual cameras are determined by minimizing the distance between the object contours and the projected visual cone for a reference view. After the camera parameters are determined, the 3D object model is constructed via the image-based visual hulls (IBVH) technique. The 3D model can be refined by integrating the multiple models reconstructed from different views. The main advantage of the proposed contour-based Structure from Reflection (SfR) algorithm is that it can achieve metric reconstruction from an uncalibrated image without feature point correspondences. Experimental results on synthetic and real images are presented to show its performance.
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来自反射的基于轮廓的结构
在本文中,我们提出了一种新的基于轮廓的算法,用于在双平面镜设置下从单幅未校准图像中重建三维物体。利用从图像中恢复的极极几何形状和镜面反射的特性,可以在不知道相机参数和镜面姿态的情况下完成任意刚体的度量重建。对于这种镜面设置,可以从物体与其反射之间的对应关系中估计出极点,并且可以从其轮廓的切线自动建立。利用镜面反射的特性以及镜面法线与极点的关系和相机的内禀关系,可以估计出相机的内禀、平面法线和虚拟相机的方位。虚拟摄像机的位置是通过最小化物体轮廓和参考视图的投影视锥之间的距离来确定的。在确定相机参数后,利用基于图像的视觉船体(IBVH)技术构建三维目标模型。通过整合从不同视图重构的多个模型,可以对三维模型进行精化。所提出的基于轮廓的反射结构(SfR)算法的主要优点是它可以从没有特征点对应的未校准图像中实现度量重建。在合成图像和真实图像上的实验结果证明了该算法的性能。
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