Detector-in-the-Loop Tracking: Active Memory Rectification for Stable Glottic Opening Localization

• URL: http://arxiv.org/abs/2602.19380v1
• Date: Sun, 22 Feb 2026 23:29:28 GMT
• Title: Detector-in-the-Loop Tracking: Active Memory Rectification for Stable Glottic Opening Localization
• Abstract summary: We propose a detector-in-the-loop framework that supervises Segment Anything Model 2(SAM2) through confidence-aligned state decisions and active memory rectification.<n>On emergency intubation videos, CL-MC achieves state-of-the-art performance, significantly reducing drift and missing rate.
• Score: 25.593059138669844
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Temporal stability in glottic opening localization remains challenging due to the complementary weaknesses of single-frame detectors and foundation-model trackers: the former lacks temporal context, while the latter suffers from memory drift. Specifically, in video laryngoscopy, rapid tissue deformation, occlusions, and visual ambiguities in emergency settings require a robust, temporally aware solution that can prevent progressive tracking errors. We propose Closed-Loop Memory Correction (CL-MC), a detector-in-the-loop framework that supervises Segment Anything Model 2(SAM2) through confidence-aligned state decisions and active memory rectification. High-confidence detections trigger semantic resets that overwrite corrupted tracker memory, effectively mitigating drift accumulation with a training-free foundation tracker in complex endoscopic scenes. On emergency intubation videos, CL-MC achieves state-of-the-art performance, significantly reducing drift and missing rate compared with the SAM2 variants and open loop based methods. Our results establish memory correction as a crucial component for reliable clinical video tracking. Our code will be available in https://github.com/huayuww/CL-MR.

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