DF

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

Usage

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

Abstract

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.

Overview

Results

Results on OOTB

Contact

If you have any questions or suggestions, feel free to contact me.
Email: yuzeng_chen@whu.edu.cn

Citation

If you find our work helpful in your research, kindly consider citing it. We appreciate your support.

@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}}

YZCU / DF