Trajectory reconstruction from non-overlapping surveillance cameras with relative depth ordering constraints

B. Micusík
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引用次数: 7

Abstract

We present a method for reconstructing a trajectory of an object moving in front of non-overlapping fully or partially calibrated cameras. The non-overlapping setup turns that problem ill-posed as no point correspondences can be established which are necessary for the well known point triangulation. The proposed solution instead builds on the assumption of trajectory smoothness and depth ordering prior information. We propose a novel formulation with a consistent minimization criterion and a way to utilize the depth ordering prior reflected by the size change of a bounding box associated to an image point being tracked. Reconstructing trajectory minimizing the trajectory smoothness, its re-projection error and employing the depth priors is casted as the Second Order Cone Program yielding a global optimum. The new formulation together with the proposed depth prior significantly improves the trajectory reconstruction in sense of accuracy and topology, and speeds up the solver. Synthetic and real experiments validate the feasibility of the proposed approach.
基于相对深度排序约束的非重叠监控摄像机轨迹重建
我们提出了一种重建在非重叠的完全或部分校准相机前运动的物体轨迹的方法。不重叠的设置使得没有点对应的病态问题可以建立,而这是众所周知的点三角剖分所必需的。该方法基于轨迹平滑和深度排序先验信息的假设。我们提出了一种新的公式,具有一致的最小化标准和一种利用深度排序先验的方法,这种先验是由与被跟踪的图像点相关的边界框的大小变化所反映的。以最小的轨迹平滑度和重投影误差重构轨迹,利用深度先验将其转化为二阶锥规划,得到全局最优解。新公式与深度先验在精度和拓扑意义上显著提高了轨迹重建,加快了求解速度。综合实验和实际实验验证了该方法的可行性。
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