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A Narrow Deep Learning Assisted Visual Tracking with Joint Features
2020
Mathematical Problems in Engineering
A robust tracking method is proposed for complex visual sequences. Different from time-consuming offline training in current deep tracking, we design a simple two-layer online learning network which fuses local convolution features and global handcrafted features together to give the robust representation for visual tracking. The target state estimation is modeled by an adaptive Gaussian mixture. The motion information is used to direct the distribution of the candidate samples effectively. And
doi:10.1155/2020/8659890
fatcat:6e5egqqwhjdr7ogfkrc7bdrkui