Visualization of Automated and Manual Trajectories in Wide-Area Motion Imagery

The task of automated object tracking and performance assessment in low frame rate, persistent, wide spatial coverage motion imagery is an emerging research domain. The collection of hundreds to tens of thousands of dense trajectories produced by such automatic algorithms along with the subset of manually verified tracks across several coordinate systems require new tools for effective human computer interfaces and exploratory trajectory visualization. We describe an interactive visualization system that supports very large gig pixel per frame video, facilitates rapid, intuitive monitoring and analysis of tracking algorithm execution, provides visual methods for the inter comparison of very long manual tracks with multi segmented automatic tracker outputs, and a flexible KOLAM Tracking Simulator (KOLAM-TS) middleware that generates visualization data by automating the object tracker performance testing and benchmarking process.