The official implementation for "Single Object Tracking in Satellite Videos: A Correlation Filter-Based Dual-Flow Tracker", IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (JSTARS), 2022.
- Authors: Yuzeng Chen, Yuqi Tang*, Zhiyong Yin, Te Han, Bin Zou, and Huihui Feng
- Central South University and Key Laboratory of Metallogenic Prediction of Nonferrous Metals and Geological Environment Monitoring
- We've updated and embedded DF tracker into the OOTB project
- OOTB is a benchmark including oriented satellite video datasets and evaluation benchmark
- Codes for DF tracker is in the path
\tracker_benchmark_v1.0\trackers\DF - Download the related OOTB dataset on Baidu Cloud Disk (code: OOTB)
- Run the
\tracker_benchmark_v1.0\main_running.m - Results are saved in
\tracker_benchmark_v1.0\results\results_OPE_ootb - Evaluation of the DF tracker. Run
\tracker_benchmark_v1.0\perfPlot.m
Satellite video (SV) can acquire rich spatiotemporal information on the Earth. Single object tracking (SOT) in SVs enables the continuous acquisition of the position and range of a specific object, expanding the field of remote-sensing applications. In SVs, objects are small with limited features and vulnerable to tracking drift. In this paper, a correlation filter-based dual-flow (DF) tracker is proposed to explore how the hybridization of spatial-spectral feature fusion and motion model can boost tracking. To represent small objects, the DF adaptively fuses complementary features using a state-aware indicator in feature flow. In motion flow, the indicator perceives the confidence of the feature flow. A dual-mode prediction model is then constructed to simulate the object¡¯s motion pattern, and cooperate linear and non-linear motion patterns to implement SOT in SVs. The ablation experiments demonstrate the dual-flow contributes to tracking. Experimental comparisons on 14 real SVs captured by the Jilin-1 satellite constellation show that DF achieves optimal performance with an area under the curve of 0.912 in the precision plot, 0.700 in the success plot, and a speed of 155.2 frames per second. This work would encourage the development of remote-sensing ground surveillance.
- Results on OOTB
If you have any questions or suggestions, feel free to contact me.
Email: yuzeng_chen@whu.edu.cn
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@ARTICLE{9803284,
author={Chen, Yuzeng and Tang, Yuqi and Yin, Zhiyong and Han, Te and Zou, Bin and Feng, Huihui},
journal={IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing},
title={Single Object Tracking in Satellite Videos: A Correlation Filter-Based Dual-Flow Tracker},
year={2022},
volume={15},
number={},
pages={6687-6698},
keywords={Correlation;Videos;Remote sensing;Satellites;Object tracking;Adaptation models;Optical filters;Correlation filter (CF);motion model;satellite video (SV);state-aware indicator (SAI);single object tracking (SOT)},
doi={10.1109/JSTARS.2022.3185328}}