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Active structure from motion for spherical and cylindrical targets

机译:球形和圆柱形目标运动产生的主动结构

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Structure estimation from motion (SfM) is a classical and well-studied problem in computer and robot vision, and many solutions have been proposed to treat it as a recursive filtering/estimation task. However, the issue of actively optimizing the transient response of the SfM estimation error has not received a comparable attention. In this paper, we provide an experimental validation of a recently proposed nonlinear active SfM strategy via two concrete applications: 3D structure estimation for a spherical and a cylindrical target. The experimental results fully support the theoretical analysis and clearly show the benefits of the proposed active strategy. Indeed, by suitably acting on the camera motion and estimation gains, it is possible to assign the error transient response and make it equivalent to that of a reference linear second-order system with desired poles.
机译:基于运动的结构估计(SfM)是计算机和机器人视觉中的经典且经过充分研究的问题,已经提出了许多解决方案,将其视为递归过滤/估计任务。但是,积极优化SfM估计误差的瞬态响应的问题尚未引起类似的关注。在本文中,我们通过两个具体的应用程序对最近提出的非线性主动SfM策略进行了实验验证:球形和圆柱形目标的3D结构估计。实验结果完全支持理论分析,并清楚地表明了所提出的主动策略的好处。实际上,通过适当地作用于摄像机的运动和估计增益,可以分配误差瞬态响应并使之等效于具有所需极点的参考线性二阶系统的误差瞬态响应。

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