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论文类型：期刊论文

发表时间：2017-04-01

发表刊物：IMAGE AND VISION COMPUTING

收录刊物：SCIE、EI、Scopus

卷号：60

期号：,SI

页面范围：124-133

ISSN号：0262-8856

关键字：Visual tracking; Structural information; Patch-based model; Linear programming

摘要：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.