Object Tracking via Dual Linear Structured SVM and Explicit Feature Map

@article{Ning2016ObjectTV,
  title={Object Tracking via Dual Linear Structured SVM and Explicit Feature Map},
  author={Jifeng Ning and Jimei Yang and Shaojie Jiang and Lei Zhang and Ming-Hsuan Yang},
  journal={2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
  year={2016},
  pages={4266-4274}
}
Structured support vector machine (SSVM) based methods have demonstrated encouraging performance in recent object tracking benchmarks. However, the complex and expensive optimization limits their deployment in real-world applications. In this paper, we present a simple yet efficient dual linear SSVM (DLSSVM) algorithm to enable fast learning and execution during tracking. By analyzing the dual variables, we propose a primal classifier update formula where the learning step size is computed in… CONTINUE READING
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