Weak-Observation-Aware Multi-Object Tracking in Satellite Video with Temporal Evidence and Trajectory Reliability.
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| Title: | Weak-Observation-Aware Multi-Object Tracking in Satellite Video with Temporal Evidence and Trajectory Reliability. |
|---|---|
| Authors: | Hu, Fen1 (AUTHOR), Yang, Peng1 (AUTHOR), Dou, Jie1 (AUTHOR), Dou, Lei1 (AUTHOR) doulei@njust.edu.cn |
| Source: | Remote Sensing. Sep2026, Vol. 18 Issue 18, p3084. 26p. |
| Subjects: | Artificial satellite tracking, Tracking control systems |
| Abstract: | Highlights: What are the main findings? A layered weak-observation framework combines motion-aligned temporal-prior modeling with reliability-guided trajectory association and state updating. The proposed method achieves a multiple object tracking accuracy (MOTA) of 72.5% and an identity F1 score (IDF1) of 81.1% on VISO and obtains the best MOTA and IDF1 for the airplane and vehicle categories of SATMTB-MOT. What are the implications of the main findings? Motion-aligned temporal evidence can recover weak target observations without indiscriminately propagating background responses. Candidate-reliability control provides a practical balance between weak-target recovery and identity preservation in satellite-video tracking. Multi-object tracking (MOT) in satellite video is fundamentally limited by low target observability: genuine targets often produce weak and unstable responses, while structured backgrounds can generate persistent target-like interference, leading to missed detections, fragmented trajectories, and identity switches. To address this ambiguity, we propose a weak-observation-aware and reliability-guided framework with a layered two-stage design: the front end enhances weak observations over short temporal windows, whereas the back end controls their use for long-term trajectory association and state updating according to their reliability. The front-end Temporal Prior Module (TPM) constructs a structure-aware temporal prior from motion-aligned historical evidence, strengthening weak-target responses while limiting the propagation of structured-background interference. The back-end Satellite Weak-Observation Reliability-Guided Tracker (SWRT) introduces active-track support into short-window reasoning and combines current, short-term, and long-term evidence into a candidate-reliability score that regulates association eligibility and state-update strength. On VISO, the proposed method achieves a multiple object tracking accuracy (MOTA) of 72.5% and an identity F1 score (IDF1) of 81.1%. On SATMTB-MOT, it achieves the best MOTA and IDF1 for airplanes and vehicles and remains competitive for ships among the compared methods. These results demonstrate that this layered design achieves a better balance between target recovery and identity preservation under low-observability conditions. [ABSTRACT FROM AUTHOR] |
| Copyright of Remote Sensing is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
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| Header | DbId: egs DbLabel: Engineering Source An: 197381207 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Weak-Observation-Aware Multi-Object Tracking in Satellite Video with Temporal Evidence and Trajectory Reliability. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Hu%2C+Fen%22">Hu, Fen</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Yang%2C+Peng%22">Yang, Peng</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Dou%2C+Jie%22">Dou, Jie</searchLink><relatesTo>1</relatesTo> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Dou%2C+Lei%22">Dou, Lei</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> doulei@njust.edu.cn</i> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Remote+Sensing%22">Remote Sensing</searchLink>. Sep2026, Vol. 18 Issue 18, p3084. 26p. – Name: Subject Label: Subjects Group: Su Data: <searchLink fieldCode="DE" term="%22Artificial+satellite+tracking%22">Artificial satellite tracking</searchLink><br /><searchLink fieldCode="DE" term="%22Tracking+control+systems%22">Tracking control systems</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: Highlights: What are the main findings? A layered weak-observation framework combines motion-aligned temporal-prior modeling with reliability-guided trajectory association and state updating. The proposed method achieves a multiple object tracking accuracy (MOTA) of 72.5% and an identity F1 score (IDF1) of 81.1% on VISO and obtains the best MOTA and IDF1 for the airplane and vehicle categories of SATMTB-MOT. What are the implications of the main findings? Motion-aligned temporal evidence can recover weak target observations without indiscriminately propagating background responses. Candidate-reliability control provides a practical balance between weak-target recovery and identity preservation in satellite-video tracking. Multi-object tracking (MOT) in satellite video is fundamentally limited by low target observability: genuine targets often produce weak and unstable responses, while structured backgrounds can generate persistent target-like interference, leading to missed detections, fragmented trajectories, and identity switches. To address this ambiguity, we propose a weak-observation-aware and reliability-guided framework with a layered two-stage design: the front end enhances weak observations over short temporal windows, whereas the back end controls their use for long-term trajectory association and state updating according to their reliability. The front-end Temporal Prior Module (TPM) constructs a structure-aware temporal prior from motion-aligned historical evidence, strengthening weak-target responses while limiting the propagation of structured-background interference. The back-end Satellite Weak-Observation Reliability-Guided Tracker (SWRT) introduces active-track support into short-window reasoning and combines current, short-term, and long-term evidence into a candidate-reliability score that regulates association eligibility and state-update strength. On VISO, the proposed method achieves a multiple object tracking accuracy (MOTA) of 72.5% and an identity F1 score (IDF1) of 81.1%. On SATMTB-MOT, it achieves the best MOTA and IDF1 for airplanes and vehicles and remains competitive for ships among the compared methods. These results demonstrate that this layered design achieves a better balance between target recovery and identity preservation under low-observability conditions. [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Remote Sensing is the property of MDPI and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.3390/rs18183084 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 26 StartPage: 3084 Subjects: – SubjectFull: Artificial satellite tracking Type: general – SubjectFull: Tracking control systems Type: general Titles: – TitleFull: Weak-Observation-Aware Multi-Object Tracking in Satellite Video with Temporal Evidence and Trajectory Reliability. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Hu, Fen – PersonEntity: Name: NameFull: Yang, Peng – PersonEntity: Name: NameFull: Dou, Jie – PersonEntity: Name: NameFull: Dou, Lei IsPartOfRelationships: – BibEntity: Dates: – D: 15 M: 09 Text: Sep2026 Type: published Y: 2026 Identifiers: – Type: issn-print Value: 20724292 Numbering: – Type: volume Value: 18 – Type: issue Value: 18 Titles: – TitleFull: Remote Sensing Type: main |
| ResultId | 1 |
