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Three-dimensional trajectory estimation from image position and velocity

机译:基于图像位置和速度的三维轨迹估计

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摘要

A recursive algorithm for estimating the three-dimensional trajectory and structure of a moving rigid object in an image sequence has been previously developed by Broida, Chandrashekhar, and Chellappa [1990]. Since then, steady advances have occurred in the calculation of optical flow. This work improves 3D motion trajectory and structure estimation by incorporating optical flow into the estimation framework. The new solution combines optical flow and feature point measurements and determines their statistical relationship. The feasibility of a hybrid feature point/optical flow algorithm, demonstrated through detailed simulation on synthetic and real image sequences, significantly lowers bias and mean squared error in trajectory estimation over the feature-based approach.
机译:Broida,Chandrashekhar和Chellappa [1990]先前已经开发出一种递归算法,用于估计图像序列中运动的刚性物体的三维轨迹和结构。从那时起,在光流的计算中出现了稳定的进步。通过将光流合并到估算框架中,这项工作改进了3D运动轨迹和结构估算。新的解决方案结合了光流和特征点测量,并确定了它们的统计关系。通过对合成和真实图像序列进行详细的仿真,证明了混合特征点/光学流算法的可行性,与基于特征的方法相比,可显着降低轨迹估计中的偏差和均方误差。

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