A Spatial-Aware Tracker
Zhiyong Li, Ximing Xiang, Ke Nai, Shilong Jiang · 2019
In this paper, a novel spatial-aware tracker (SAT), which utilizes the Siamese network and multiple correlation filters, is proposed to deal with fast motion and model drift problem in visual tracking. Specifically, the Siamese network is first used by an adaptive spatial search strategy to detect the target object in larger search areas. An extended search patch is generated if the target position obtained by the Siamese network is far away from the previous target position. Then, multiple correlation filters perform detection operations on both the extended search patch and the original search patch. With the proposed spatial selection scheme, SAT can accurately track the target object in challenging tracking scenes. By taking advantage of the Siamese network and multiple correlation filters, the proposed SAT tracker can effectively deal with fast motion and model drift problems to achieve better tracking performance. Extensive experimental results demonstrate that the proposed SAT tracker performs superiorly against several state-of-the-art trackers on OTB-2015 tracking benchmark.