Propagating spatio-temporal state and progressively associating trajectory for satellite video multi-object tracking

影响因子：7.5

DOI码：10.1016/j.eswa.2025.130507

发表刊物：Expert Systems with Applications

摘要：High-resolution video satellites enable large-view dynamic monitoring for earth observation. Among satellite video interpretation techniques, multi-object tracking (MOT) receives growing attention for its foundational role. Rigid targets in satellite videos exhibit strong inter-frame appearance and posture consistency, showing quasi-linear trajectories with constrained displacements. Inspired by these kinematic characteristics, this paper introduces an online end-to-end Propagating Spatio-temporal State and Progressively Associating Trajectory MOT (PS2PAT-MOT) framework. It consists of a detection branch for locating multi-category and multi-target objects in current frame, and a correlation branch using an inter-frame spatio-temporal state propagation (STSP) module to propagate location and appearance information and encode same-target correlations between adjacent frames. Detection and correlation outputs from both branches undergo affinity calculation, while the Progressively Associating Trajectory (PAT) strategy generates continuous tracklets using differentiated association thresholds for distinct trajectory segments. Experimental results on two publicly available AIR-MOT, SAT-MTB, and a self-built LV-SatMOT (Large-View Satellite video MOT) datasets demonstrate the effectiveness of the proposed PS2PAT-MOT framework. Codes are available at: https://github.com/HELOBILLY/PS2PAT-MOT.

合写作者：Xiaodong Zhang, Lei Ding, Xiangyun Liu, Jun Lu

论文类型：期刊论文

通讯作者：Haitao Guo, Guanzhou Chen

文献类型：J

卷号：301

页面范围：130507

ISSN号：0957-4174

是否译文：否

发表时间：2026-03-10