Target Detection and Tracking in High-Resolution Aerial Images using Contour-Based Spatial Model and Correlation Tracker

This project aims at developing a contour-based spatial model which can detect geospatial targets accurately in high-resolution Aerial images. The detected targets are tracked using target tracking Correlation Algorithm. To detect the geospatial targets with complex structures, each image was partitioned into pieces as target candidate regions using multiple segmentations at first. Then, the automatic identification of target seed regions is achieved by computing the similarity of the contour information with the target template using dynamic programming. Finally, the contour-based similarity was further updated and combined with spatial relationships to figure out the missing parts. In this way, a more accurate target detection result can be achieved. The detected target further has to be monitored for its movements, this is achieved by implementing a correlation based tracking algorithm which efficiently tracks the target movements in successive image frames and its 2-D coordinates are plotted. The 2-D coordinates gives the observer a view of the Target movements and intentions.