To fully develop the complementary advantages of different visual features and to improve the robustness of multi-feature fusions, we propose a robust correlation filter tracker with adaptive multi-complementary features fusion based on game theory. By combining the complementary features selected from handcrafted features and convolution features, our method constructs two robust combined features in the tracking framework of discriminative correlation filters (DCFs). In addition, by utilizing game theory, the two combined features are regarded as two sides of the game, achieving the best balance through continuous gaming throughout the tracking process and thus obtaining a more robust fused feature. The experimental results obtained on the OTB2015 benchmark dataset demonstrate that our tracker improves the robustness of object tracking in complex scenarios, such as occlusion and deformation, and performs favorably against eight state-of-the-art methods.

中文翻译：

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基于博弈论的多互补特征自适应融合实现鲁棒视觉目标跟踪

为了充分发挥不同视觉特征的互补优势，提高多特征融合的鲁棒性，我们提出了一种基于博弈论的自适应多互补特征融合的鲁棒相关滤波器跟踪器。通过结合从手工特征和卷积特征中选择的互补特征，我们的方法在判别相关滤波器 (DCF) 的跟踪框架中构建了两个强大的组合特征。此外，利用博弈论，将两个组合特征视为博弈的两个方面，在整个跟踪过程中通过连续博弈达到最佳平衡，从而获得更鲁棒的融合特征。