Detection and tracking of platforms above sea-level in infrared and visual band videos using Bag-of-Features technique with scale invariant feature transform

In this study, platforms above sea-level are detected and tracked using Bag-of-Features technique (BoF) with scale-invariant feature transform (SIFT) in infrared (IR) and visual (VIS) band videos. Features in the training set corresponding to platforms above sea-level and background are firstly clustered in offline mode and these features are used for target detection using BoF technique. With these features, targets are matched in the subsequent frames and the matchings are pruned with a set of heuristic rules. Target tracking performance is compared with respect to the ground-truth target positions for different IR and VIS band videos obtained in field trials and with an optic-flow based method. The results show that platforms above sea-level can be detected and tracked using SIFT features and BoF technique with high accuracy.