  Multi-spectral sensors consisting of a standard (visible-light) camera and a
long-wave infrared camera can simultaneously provide both visible and thermal
images. Since thermal images are independent from environmental illumination,
they can help to overcome certain limitations of standard cameras under
complicated illumination conditions. However, due to the difference in the
information source of the two types of cameras, their images usually share very
low texture similarity. Hence, traditional texture-based feature matching
methods cannot be directly applied to obtain stereo correspondences. To tackle
this problem, a multi-spectral visual odometry method without explicit stereo
matching is proposed in this paper. Bundle adjustment of multi-view stereo is
performed on the visible and the thermal images using direct image alignment.
Scale drift can be avoided by additional temporal observations of map points
with the fixed-baseline stereo. Experimental results indicate that the proposed
method can provide accurate visual odometry results with recovered metric
scale. Moreover, the proposed method can also provide a metric 3D
reconstruction in semi-dense density with multi-spectral information, which is
not available from existing multi-spectral methods.
