  Thermal infrared cameras are increasingly being used in various applications
such as robot vision, industrial inspection and medical imaging, thanks to
their improved resolution and portability. However, the performance of
traditional computer vision techniques developed for electro-optical imagery
does not directly translate to the thermal domain due to two major reasons:
these algorithms require photometric assumptions to hold, and methods for
photometric calibration of RGB cameras cannot be applied to thermal-infrared
cameras due to difference in data acquisition and sensor phenomenology. In this
paper, we take a step in this direction, and introduce a novel algorithm for
online photometric calibration of thermal-infrared cameras. Our proposed method
does not require any specific driver/hardware support and hence can be applied
to any commercial off-the-shelf thermal IR camera. We present this in the
context of visual odometry and SLAM algorithms, and demonstrate the efficacy of
our proposed system through extensive experiments for both standard benchmark
datasets, and real-world field tests with a thermal-infrared camera in natural
outdoor environments.
