The fragments of trajectories result when tracking temporarily fails, breaking a trajectory into pieces, or when different parts of the same object are temporarily tracked, resulting in duplicates of short pieces of the full length trajectory. The results in Table 1 show the rates of missed detection for three categories of objects. As seen, the algorithm is more successful in tracking vehicles than people. This is due to problems in segmentation resulting from the more complex motions of people in the scene, and to their smaller size. The imprecision and noisiness of the MPEG motion estimates is simply inadequate to describe these motions correctly, or to recognize them at all.
Tracking fails as well when motions are too similar, or occlusions too great.
The segmentation and tracking algorithms work easily in real time. The velocity estimator was tested as well. Recall that a user can request that queries be sorted according to velocity. Various trajectory queries were posed to the database with this ordering requested. The average velocity of the objects was estimated by the human operator by measuring the distance traveled by an object, and the duration of its travel.