文章基本信息

标题：An improved spatio-temporal context tracking algorithm based on scale correlation filter:
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作者：Wei-Guang Li ; Hao Wan
期刊名称：Advances in Mechanical Engineering
印刷版ISSN：1687-8140
电子版ISSN：1687-8140
出版年度：2019
卷号：11
期号：2
DOI：10.1177/1687814019825903
语种：English
出版社：Sage Publications Ltd.
摘要：Spatio-temporal context algorithm is commonly used in geology and has been introduced into the field of target tracking in recent years. The algorithm improved the robustness of visual tracking through dense contextual information around the target and thus achieved great tracking results. However, updating errors may occur in spatio-temporal context algorithm when the target has rapid changes in scale and appearance, resulting in the algorithm cannot extract the target area accurately and completely. In order to overcome this problem, this article proposes an improved spatio-temporal context algorithm based on scale correlation filter. First of all, the algorithm extracts samples of different scales around the target after the target is settled by spatio-temporal context algorithm and then forms the pyramid of scale characteristics through samples extracted by histogram of oriented gradients operator. Second, the best scale parameter will be achieved by means of scale correlation filter to update the sca...
关键词：Visual tracking; scale correlation filter; spatio-temporal context; robust tracking; feature pyramid