The analogy
between ground truth values and Kalman approximation
are shown in Fig. 3 and Fig. 4, respectively.
From both
figures, it becomes evident that the Kalman filter tracks
the detected object with well enough approximation. In
these two figures, large picks in ground truth data
represents detection failure where tracking algorithm
continues to track using correlation information of
previously detected object regions.