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. Controlled ablations on a fixed validation split and evaluation on the official PBVS Thermal Pedestrian MOT benchmark show that the main identity gains arise from conservative relinking, improving IDF1 from 82.25 to 84.93 while preserving MOTA, whereas many heuristic thresholds remain stable across broad operating ranges. These results suggest that, in low-information thermal imagery, robust identity recovery can be achieved more effectively through high-precision trajectory relinking than through increasing tracker complexity. These results provide a controlled analysis of identity recovery in thermal video, showing that scene-level spatial-temporal consistency plays a dominant role in identity continuity compared to local frame-to-frame association.

翻译：热红外行人多目标跟踪仍具挑战性，因为微弱的外观线索和频繁的检测中断会导致严重的轨迹碎片化。我们研究轻量级后处理能否在不依赖重识别模型或复杂在线关联的情况下恢复身份连续性。基于YOLOv8和SORT基线，我们添加了一个模块化的身份修复后端，包含基于时间、空间、运动和边界线索的在线短间隔重映射和离线轨迹片段重连。在固定验证集上的受控消融实验及在官方PBVS热红外行人多目标跟踪基准上的评估表明，身份增益主要源于保守重连，将IDF1从82.25提升至84.93，同时保持MOTA不变，而多数启发式阈值在大范围操作区间内保持稳定。这些结果表明，在低信息量的热红外影像中，通过高精度轨迹重连比增加跟踪器复杂度能更有效地实现鲁棒的身份恢复。本工作为热红外视频中的身份恢复提供了受控分析，表明相较于局部帧间关联，场景级时空一致性对身份连续性起主导作用。