Abstract：In order to overcome the disadvantages of just adopting single feature and lacking of local structure information in traditional tracking algorithms，a hybrid model visual tracking algorithm based on multi-feature fusion is proposed.Firstly，it structures a robust appearance model via integrating the local appearance model of intensity together with the global templates of color histograms and histogram of oriented gradient （HOG）.Then，a strategy of outlier rejection is also proposed，which divides the sparse coefficient into two collaborative components and imposes the l2，1 mixed-norm regularization.The experimental results on benchmark dataset show that the proposed method is more accurate and robust in dealing with illumination change and occlusion.
王琳,陈志国,孙俊. 多特征融合的混合模型视频跟踪算法[J]. 小型微型计算机系统, 2017, 38(12): 2689-2693.
WANG Lin,CHEN Zhi-guo,SUN Jun. Hybrid Model Visual Tracking Algorithm Based on Multi-feature Fusion. Journal of Chinese Computer Systems, 2017, 38(12): 2689-2693.
2017, Vol. 38 
