Automatic Failure Recovery and Re-Initialization for Online UAV Tracking with Joint Scale and Aspect Ratio Optimization
| Autor: | Changhong Fu, Jin Jin, Fangqiang Ding, Chen Feng, Yiming Li |
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| Rok vydání: | 2020 |
| Předmět: |
FOS: Computer and information sciences
68T40 Computer science Computer Vision and Pattern Recognition (cs.CV) 2D Filters Real-time computing Computer Science - Computer Vision and Pattern Recognition Initialization ComputerApplications_COMPUTERSINOTHERSYSTEMS 02 engineering and technology Filter (signal processing) Tracking (particle physics) Visualization Domain (software engineering) F.2.2 I.4.9 Computer Science - Robotics 0202 electrical engineering electronic engineering information engineering Eye tracking 020201 artificial intelligence & image processing Robotics (cs.RO) |
| Zdroj: | IROS |
| DOI: | 10.1109/iros45743.2020.9341744 |
| Popis: | Current unmanned aerial vehicle (UAV) visual tracking algorithms are primarily limited with respect to: (i) the kind of size variation they can deal with, (ii) the implementation speed which hardly meets the real-time requirement. In this work, a real-time UAV tracking algorithm with powerful size estimation ability is proposed. Specifically, the overall tracking task is allocated to two 2D filters: (i) translation filter for location prediction in the space domain, (ii) size filter for scale and aspect ratio optimization in the size domain. Besides, an efficient two-stage re-detection strategy is introduced for long-term UAV tracking tasks. Large-scale experiments on four UAV benchmarks demonstrate the superiority of the presented method which has computation feasibility on a low-cost CPU. 8pages, 8 figures, accepted by 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems(IROS) |
| Databáze: | OpenAIRE |
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