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3D Reconstruction of Background and Objects Moving on Ground Plane Viewed from a Moving Camera

机译:3d背景和物体的重建在从移动的照相机观看的地面飞机上移动

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We present a novel method to obtain a 3D Euclidean reconstruction of both the background and moving objects in a video sequence. We assume that, multiple objects are moving rigidly on a ground plane observed by a moving camera. The video sequence is first segmented into static background and motion blobs by a homography-based motion segmentation method. Then classical "Structure from Motion" (SfM) techniques are applied to obtain a Euclidean reconstruction of the static background. The motion blob corresponding to each moving object is treated as if there were a static object observed by a hypothetical moving camera, called a "virtual camera". This virtual camera shares the same intrinsic parameters with the real camera but moves differently due to object motion. The same SfM techniques are applied to estimate the 3D shape of each moving object and the pose of the virtual camera. We show that the unknown scale of moving objects can be approximately determined by the ground plane, which is a key contribution of this paper. Another key contribution is that we prove that the 3D motion of moving objects can be solved from the virtual camera motion with a linear constraint imposed on the object translation. In our approach, a planar-translation constraint is formulated: "the 3D instantaneous translation of moving objects must be parallel to the ground plane ". Results on real-world video sequences demonstrate the effectiveness and robustness of our approach.
机译:我们提出了一种新的方法,以获得视频序列中的背景和移动物体的3D欧几里德重建。我们假设,多个物体在由移动相机观察到的地面平面上刚性地移动。通过基于同位的运动分段方法,首先将视频序列分段为静态背景和运动BLOB。然后应用古典“来自运动”(SFM)技术的古典“结构来获得静态背景的欧几里德重建。对应于每个移动物体的运动BLOB被视为被称为“虚拟摄像机”的假设移动摄像机观察到的静态对象。此虚拟摄像机与真正的相机共享相同的内部参数,但由于对象运动而不同地移动。应用相同的SFM技术来估计每个移动物体的3D形状和虚拟相机的姿势。我们表明,移动物体的未知等级可以大致由地平面确定,这是本文的主要贡献。另一个主要贡献是,我们证明了移动物体的3D运动可以从虚拟摄像机运动中求解对象转换上的线性约束。在我们的方法中,制定了平面翻译约束:“移动物体的3D瞬时翻译必须平行于地平面”。现实世界视频序列的结果展示了我们方法的有效性和稳健性。

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