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• W2890730827 abstract "How to effectively utilize the temporal information in video has been an important problem in visual tracking. In this paper, we try to address this problem from two aspects. At first, we use optical flow to take advantage of the inter-frame information, when we obtain the position of the last frame, we predict the approximate location in present frame by calculating the optical flow and generate samples around it. Secondly, we use the tracked patches as reference to identify the target better. We designed a Siamese network which take image pairs consisted of exemplars and samples as inputs, the objective function is also modified by adding a priori probability. Further, we conducted experiments on the OTB benchmark and achieve competitive result both on accuracy and robustness, which demonstrate the effectiveness of our proposed algorithm." @default.
• W2890730827 created "2018-09-27" @default.
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• W2890730827 date "2018-10-01" @default.
• W2890730827 modified "2023-09-26" @default.
• W2890730827 title "Flow Guided Siamese Network for Visual Tracking" @default.
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• W2890730827 doi "https://doi.org/10.1109/icip.2018.8451324" @default.
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