Background estimation under rapid gain change in thermal imagery

We consider detection of moving ground vehicles in airborne sequences recorded by a thermal sensor with automatic gain control, using an approach that integrates dense optic flow over time to maintain a model of background appearance and a foreground occlusion layer mask. However, the automatic gain control of the thermal sensor introduces rapid changes in intensity that makes this difficult. In this paper we show that an intensity-clipped affine model of sensor gain is sufficient to describe the behavior of our thermal sensor. We develop a method for gain estimation and compensation that uses sparse flow of corner features to compute the affine background scene motion that brings pairs of frames into alignment prior to estimating change in pixel brightness. Dense optic flow and background appearance modeling is then performed on these motioncompensated and brightness-compensated frames. Experimental results demonstrate that the resulting algorithm can segment ground vehicles f...

• Type: Journal
• Year: 2007
• Where: CVIU
• Authors: Hulya Yalcin, Robert T. Collins, Martial Hebert
• Keywords: Automatic Gain, CVIU 2007, Dense Optic flow, Thermal Sensor