1) "Background Estimation under Rapid Gain Change in Thermal Imagery", Hulya Yalcin, Robert Collins and Martial Hebert, Carnegie Mellon University, and Penn State University, Pittsburgh, USA
1) "Background Estimation under Rapid Gain Change in Thermal Imagery",
Hulya Yalcin, Robert Collins and Martial Hebert,
Carnegie Mellon University, and Penn State University, Pittsburgh, USA
Abstract:
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 motion compensated
and brightness-compensated frames. Experimental results demonstrate that the
resulting algorithm can segment ground vehicles from thermal airborne video
while building a mosaic of the background layer, despite the presence of rapid gain changes.
2) "Spaceborne Traffic Monitoring with Dual Channel Synthetic
Aperture Radar - Theory and Experiments",
Stefan Hinz, Franz Meyer, Richard Bamler and Andreas Laika,
Remote Sensing Technology, and German Aerospace Center, Germany
Abstract:
This paper revises the theoretical background for upcoming dual-channel Radar satellite
missions to monitor traffic from space. As it is well-known, an object moving with a
velocity deviating from the assumptions incorporated in the focusing process will
generally appear both displaced and blurred in the azimuth direction. To study the
impact of these (and related) distortions in focused SAR images, the analytic relations
between an arbitrarily moving point scatterer and its conjugate in the SAR image have
been reviewed and adapted to dual-channel satellite specifications. To be able to
monitor traffic under these boundary conditions in real-life situations,
a specific detection scheme is proposed. This scheme integrates complementary detection
and velocity estimation algorithms with knowledge derived from external sources as, e.g., road databases.