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Imaging"],"abstract":"<jats:p>Industrial low-altitude multi-object tracking is challenged by overhead viewpoints, dense small targets, mutual occlusion, homogeneous appearances, and domain-shifted backgrounds. Vision-language pre-trained models provide useful semantic priors, but their category-level representations can mislead instance-level association when many same-class targets are densely distributed. This study develops an OC-SORT-based framework with reliability-aware semantic gating and retrieval-augmented trajectory memory. On the MOT17 reporting split (MOT17-09\/10\/11\/13) with FRCNN detections, the FullModel achieves 46.41% MOTA, 40.00% IDF1, 34.542% HOTA, 26.686% AssA, and 382 identity switches for seed 42. Relative to fixed-weight CLIP+FAISS, it reduces identity switches and fragmentations while trading 0.84 MOTA points for a 0.68-point IDF1 gain; exact reruns with three seeds reproduce the same MOTA, IDF1, and IDSw totals. The VisDrone-derived subset is used only as an industrial low-altitude proxy stress test: its high precision coexists with very low recall, so the result exposes domain-shift limitations, rather than demonstrating deployment-level industrial performance.<\/jats:p>","DOI":"10.3390\/jimaging12090449","type":"journal-article","created":{"date-parts":[[2026,9,16]],"date-time":"2026-09-16T16:07:29Z","timestamp":1789574849000},"page":"449","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Reliability-Aware Semantic Gating with Retrieval-Augmented Association for Online Multi-Object Tracking Under Industrial Low-Altitude Proxy Conditions"],"prefix":"10.3390","volume":"12","author":[{"given":"Rongzuo","family":"Guo","sequence":"first","affiliation":[{"name":"School of Computer Science, Sichuan Normal University, Chengdu 610068, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yuhang","family":"He","sequence":"additional","affiliation":[{"name":"School of Computer Science, Sichuan Normal University, Chengdu 610068, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2026,9,16]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"845","DOI":"10.1007\/s11263-020-01393-0","article-title":"MOTChallenge: A benchmark for single-camera multiple target tracking","volume":"129","author":"Dendorfer","year":"2021","journal-title":"Int. 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