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Visual tracking with structured patch-based model
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DOI：10.1016/j.imavis.2017.01.003.png)
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摘要
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In this paper, we present a novel structured patch-based visual tracking method, which models the appearance of individual patches and their structural relationships within a unified framework. Specifically, this framework is defined as an optimal patch selection task, and can be further formulated as a linear programming problem, tractable and efficient in tracking scenario. To account for the changing appearance of the target object during tracking process, a pyramid local covariance descriptor is proposed to fuse multiple image characteristics. We compare the proposed method with other competing trackers by the recent large-scale benchmark. Extensive experimental results demonstrate that our tracker performs favorably against the state-of-the-art tracking algorithms. (C) 2017 Elsevier B.V. All rights reserved.
Keyword:
Visual tracking
Structural information
Patch-based model
Linear programming
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