Development and Analysis of a Real-Time System for Automated Detection of IED indicators from Ground Vehicles

This work proposes a real-time change detection system to be used as a vehicle-mounted early-warning system for indicators of Improvised Explosive Devices. Within the context of military route clearance, the system automatically detects suspicious changes in the environment w.r.t. a previous patrol. For this purpose, historical images of the live scene are retrieved from a database and registered to the live image through 2.5D view synthesis, using the 3D-scene geometry acquired from a stereo camera. Changes are then found using local-area statistics in the CIE-Lab color space. A set of spatio-temporal filters is used to reject irrelevant alarms, resulting in a limited set of confident changes to be presented to the operator through an interactive Graphical User Interface. Next to the algorithmic contributions, we elaborate on the real-time design, featuring GPU processing for the most time-consuming processing tasks, a pipelined architecture to increase the system throughput and we split the system into a live and offline processing chain. This way, real-time change detection at 3.5 FPS is achieved on images of 1920×1440 pixels. Finally, an extensive system validation featuring realistic experiments shows promising detection capabilities and robustness to e.g. lateral displacements of up to 6 m.