Document Type
Data
Publication Date
5-21-2025
Abstract
We present a wheel track detection system that leverages RGB-Thermal (RGB-T) imaging, where thermal channels reveal critical temperature differentials between compacted tracks and loose snow - tracks exhibit higher thermal inertia and lower reflectivity, emitting stronger radiation signatures even in visually homogeneous conditions. By fusing these distinctive thermal patterns with RGB spatial information, our method reliably identifies navigable tracks, enabling robust path-following in complete white-out conditions where snow textures and terrain features become indistinguishable.
Recommended Citation
Yang, Y.,
&
Bos, J. P.
(2025).
ThermalTrack Dataset - Testing Images.
Retrieved from: https://digitalcommons.mtu.edu/thermaltrack/17