One of the main limitations of the commonly used Absolute Trajectory Error
(ATE) is that it is highly sensitive to outliers. As a result, in the presence
of just a few outliers, it often fails to reflect the varying accuracy as the
inlier trajectory error or the number of outliers varies. In this work, we
propose an alternative error metric for evaluating the accuracy of the
reconstructed camera trajectory. Our metric, named Discernible Trajectory Error
(DTE), is computed in four steps: (1) Shift the ground-truth and estimated
trajectories such that both of their geometric medians are located at the
origin. (2) Rotate the estimated trajectory such that it minimizes the sum of
geodesic distances between the corresponding camera orientations. (3) Scale the
estimated trajectory such that the median distance of the cameras to their
geometric median is the same as that of the ground truth. (4) Compute the
distances between the corresponding cameras, and obtain the DTE by taking the
average of the mean and root-mean-square (RMS) distance. This metric is an
attractive alternative to the ATE, in that it is capable of discerning the
varying trajectory accuracy as the inlier trajectory error or the number of
outliers varies. Using the similar idea, we also propose a novel rotation error
metric, named Discernible Rotation Error (DRE), which has similar advantages to
the DTE. Furthermore, we propose a simple yet effective method for calibrating
the camera-to-marker rotation, which is needed for the computation of our
metrics. Our methods are verified through extensive simulations