电讯技术2018，Vol.58Issue(1)：66-71,6.DOI:10.3969/j.issn.1001-893x.2018.01.012
融合局部加权余弦与稀疏表示的目标跟踪算法
An Object Tracking Algorithm Fused by Weighted Local Cosine and Sparse Representation
摘要
Abstract
Focusing on the robustness problem of target tracking algorithm,this paper proposes a target tracking method based on joint model in the particle filter framework.Firstly,the target template and the candidate targets are matched by the weighted local cosine similarity.The proposed local weighted algorithm increases the weights of the candidate targets which are not affected by occlusion,deformation,etc.Secondly,the target observation model makes use of the local information of the target by sparse coding and the dictionary is not updated.The construction of the reconstruction error considers the spatial layout between the local image patches.Finally,the maximum posterior probability is used to estimate the target state.The joint model considers the current state and the original state of the target so as to improve the reliability of the observation model.The experimental results demonstrate the robustness of the algorithm.关键词
目标跟踪/局部加权/余弦相似/稀疏表示/联合模型Key words
object tracking/local weighted/cosine similarity/sparse representation/joint model分类
信息技术与安全科学引用本文复制引用
薛斌,范馨月,周非..融合局部加权余弦与稀疏表示的目标跟踪算法[J].电讯技术,2018,58(1):66-71,6.基金项目
国家自然科学基金资助项目(61471077) （61471077）
