Image change detection has long been used to detect significant events in aerial imagery, such as the arrival or departure of vehicles. Usually only the underlying structural changes are of interest, particularly for movable objects, and the challenge is to differentiate the changes of intelligence value (change detections) from incidental appearance changes (false detections). However, existing methods for automated change detection continue to be challenged by nuisance variations in operating conditions such as sensor (camera exposure, camera viewpoints), targets (occlusions, type), and the environment (illumination, shadows, weather, seasons). To overcome these problems, we propose a novel vehicle change detection method based on the detection response maps (DRM). The detector serves as an advanced filter that normalizes the images being compared specifically for object level change detection (OLCD). In contrast to current methods that compare pixel intensities, the proposed DRM-OLCD method is more robust to nuisance changes and variations in image appearance. We demonstrate object-level change detection for vehicle appearing and disappearing in electro-optical (EO) visual imagery.

Date Published: 19 June 2014
PDF: 11 pages
Proc. SPIE 9089, Geospatial InfoFusion and Video Analytics IV; and Motion Imagery for ISR and Situational Awareness II, 908906 (19 June 2014); doi: 10.1117/12.2055362

Published in SPIE Proceedings Vol. 9089:
Geospatial InfoFusion and Video Analytics IV; and Motion Imagery for ISR and Situational Awareness II
Matthew F. Pellechia; Kannappan Palaniappan; Shiloh L. Dockstader; Paul B. Deignan; Peter J. Doucette; Donnie Self, Editor(s)