This work proposes a feature-based probabilistic data association and tracking approach
(FBPDATA) for multi-object tracking. FBPDATA is based on re-identification and tracking of
individual video image points (feature points) and aims at solving the problems of partial
split (fragmented) bloated or missed detections which are due to sensory or algorithmic
restrictions limited field of view of the sensors as well as occlusion situations.
