电子学报2017，Vol.45Issue(3)：704-711,8.DOI:10.3969/j.issn.0372-2112.2017.03.030
基于最大池图匹配的形变目标跟踪方法
Deformable Object Tracking Based on Max-pooling Graph Matching
摘要
Abstract
This paper develops a novel deformable object tracking algorithm based on max-pooling graph matching,which can be applied in the scenes with large deformations and severe occlusions.The dynamic graph is built based on candidate parts extracted by over-segmentation method from searching area,namely feature representation of candidate parts and geometric structure between them.Based on max-pooling graph matching method,the matching relations between target parts and candidate parts are found to calculate the confidence map of target location.Considering both the support of holistic target and local parts,the optimal target location can be determined.Compared to state-of-the-art methods,experimental results on several deformable sequences demonstrate the effectiveness and robustness of the proposed method.关键词
视觉目标跟踪/动态图表示/最大池图匹配Key words
visual tracking/dynamic graph representation/max-pooling graph matching分类
信息技术与安全科学引用本文复制引用
王治丹,蒋建国,齐美彬..基于最大池图匹配的形变目标跟踪方法[J].电子学报,2017,45(3):704-711,8.基金项目
国家自然科学基金(No.61371155) （No.61371155）
安徽省科技攻关项目(No.1301b042023) （No.1301b042023）
