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Novel Aggregated Solutions for Robust Visual Tracking in Traffic Scenarios
Tian, Wei
2019
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This work proposes novel approaches for object tracking in challenging scenarios like severe occlusion, deteriorated vision and long range multi-object reidenti?cation. All these solutions are only based on image sequence captured by a monocular camera and do not require additional sensors. Experiments on standard benchmarks demonstrate an improved state-of-the-art performance of these approaches. Since all the presented approaches are smartly designed, they can run at a real-time speed.
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