Filter Based Estimates of Depth
نویسنده
چکیده
We compare the performance of three filters applied to a problem in computer vision, the estimation of the position and velocity of a uniformly translating point, using image measurements corrupted by Gaussian noise. We choose this very simple application in order to make the comparison between the three filters as clear as possible. The filters are (i) the optimal filter [1]; (ii) a second order approximation to the optimal filter; and (iii) the extended Kalman filter (EKF) [1,2,3]. The significance of the optimal filter is that it provides an absolute standard against which the performance of any approximating filter can be judged.
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تاریخ انتشار 2008