A Benchmark and Simulator for UAV TrackingMatthias Mueller, Neil Smith, and Bernard Ghanem

King Abdullah University of Science and Technology (KAUST)

Acknowledgements. Research reported was supported by competitive funding from King Abdullah University of Science and Technology.

UAVV Trackingg BenchmarkDataset

123 aerial sequences, >110,000 framesSeven times larger than VIVIDSecond largest object tracking dataset

EvaluationAttributes (aerial tracking)Spatial robustness,Sensitivity to frame rateLong-term tracking

Results on OTB100, UAV123 and UAV20L

6435

11

TC128

51

38

21

UAV123

72

217

OTB100

easy medium hardDifficulty is calculated as mean of precision and success score of the best tracker per sequence. Easy >90%, Medium >50%, Hard <50%.

64%

16% 9%

39%49%

89%

55%39%

23%

59%

SV ARC LR FM OCC

Attribute ComparisonOTB100 UAV123

109

6848

28 33

73

30 21 31

60 70

39

SV ARC LR FM FOC POC OV BC IV VC CM SOB

Attribute Distribution

Simulatorr (Unrealal Enginee 444)Highlights

UAV Physics SimulationVisual servoing systemFrame capture and flight loggingMATLAB/C++ integration of trackers

Synthetic Sequence GenerationCustom depth maps for any mesh/objectAutomatic ground truth annotation

Live Tracking with FeedbackPlanned path or manual control of targetUAV is controlled by tracking algorithmLive visual feedback and novel evaluation

Qualitative VisualizationGenerate UAV trajectories from log filesUser-defined camera viewsVR integration with HTC Vive

Benchmark and Simulator available at: https://goo.gl/LBC4zU