计算机工程与应用2019，Vol.55Issue(22)：106-113,224,9.DOI:10.3778/j.issn.1002-8331.1807-0234
融合稀疏重构图像显著性的相关滤波跟踪
Correlation Filter Tracking Algorithm Fusing Image Saliency via Sparse Reconstruction
摘要
Abstract
To address the problems of target deformation and poor robustness of tracking in complex environment, a cor-relation filter tracking algorithm fusing image saliency via sparse reconstruction is proposed. In the process of target tracking, background template is extracted by superpixel segmentation. Target color correlation is obtained based on sparse recon-struction. Then the correlation filter detection score is combined with the target color detection score for accurate tracking. Template update speed is adjusted by the peak sidelobe ratio which is based on the fused detection score. Meanwhile, a center prior is established to correct the sparse reconstruction based saliency map. The proposed target tracking frame-work can adapt to deformation, illumination and other complexities. Experiments show that this algorithm is superior to other state-of-art tracking algorithms in terms of accuracy and robustness.关键词
目标跟踪/相关滤波/稀疏重构/中心先验Key words
target tracking/correlation filter/sparse reconstruction/center prior分类
信息技术与安全科学引用本文复制引用
谢瑜,陈莹..融合稀疏重构图像显著性的相关滤波跟踪[J].计算机工程与应用,2019,55(22):106-113,224,9.基金项目
国家自然科学基金(No.61573168) （No.61573168）
江苏省六大人才高峰资助项目(No.2015-WLW-004). （No.2015-WLW-004）
