Tactical 3D model generation using structure-from-motion on video from unmanned systems

Abstract

Unmanned systems have been cited as one of the future enablers of all the services to assist the warfighter in dominating the battlespace. The potential benefits of unmanned systems are being closely investigated -from providing increased and potentially stealthy surveillance, removing the warfighter from harms way, to reducing the manpower required to complete a specific job. In many instances, data obtained from an unmanned system is used sparingly, being applied only to the mission at hand. Other potential benefits to be gained from the data are overlooked and, after completion of the mission, the data is often discarded or lost. However, this data can be further exploited to offer tremendous tactical, operational, and strategic value. To show the potential value of this otherwise lost data, we designed a system that persistently stores the data in its original format from the unmanned vehicle and then generates a new, innovative data medium for further analysis. The system streams imagery and video from an unmanned system (original data format) and then constructs a 3D model (new data medium) using structure-from-motion. The 3D generated model provides warfighters additional situational awareness, tactical and strategic advantages that the original video stream lacks. We present our results using simulated unmanned vehicle data with Google Earth™ providing the imagery as well as real-world data, including data captured from an unmanned aerial vehicle flight.