AI RESEARCH
A Dual-Stream Transformer Architecture for Illumination-Invariant TIR-LiDAR Person Tracking
arXiv CS.CV
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ArXi:2604.00363v1 Announce Type: cross Robust person tracking is a critical capability for autonomous mobile robots operating in diverse and unpredictable environments. While RGB-D tracking has shown high precision, its performance severely degrades under challenging illumination conditions, such as total darkness or intense backlighting. To achieve all-weather robustness, this paper proposes a novel Thermal-Infrared and Depth (TIR-D) tracking architecture that leverages the standard sensor suite of SLAM-capable robots, namely LiDAR and TIR cameras.