AI RESEARCH
Understanding Identity Continuity in Thermal Video through Scene-Level Consistency
arXiv CS.AI
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ArXi:2606.01694v1 Announce Type: cross Thermal pedestrian MOT remains challenging because weak appearance cues and frequent detection interruptions cause severe trajectory fragmentation. We study whether lightweight post-processing can recover identity continuity without relying on heavy re-identification models or complex online association. Starting from a YOLOv8 and SORT baseline, we add a modular identity-repair backend consisting of online short-gap remapping and offline tracklet relinking based on temporal, spatial, motion, and border cues.