计算机工程与应用Issue(12)：189-193,234,6.DOI:10.3778/j.issn.1002-8331.1307-0350
特征加权融合的在线多示例学习跟踪算法
Object tracking based on online multiple instance learning with feature weighted fusion
摘要
Abstract
For the object tracking problems in computer vision, feature Weighted Fusion online Multiple Instance Learning tracking algorithm(WFMIL)is proposed. WFMIL trains two features(Hog and Haar)classifier separately by multiple instance learning method. In the tracking process, they are integrated into a strong classifier by the linear operation. While in the learn-ing process, weight is introduced into instances of positive package. Experimental results show that WFMIL can solve the object drift and has a certain robustness in handling occlusion, target abrupt motion, illumination change, and motion blur.关键词
特征融合/在线多示例学习/目标跟踪Key words
feature fusion/online multiple instance learning/object tracking分类
信息技术与安全科学引用本文复制引用
刘薇,戴平阳,李翠华..特征加权融合的在线多示例学习跟踪算法[J].计算机工程与应用,2015,(12):189-193,234,6.基金项目
国家自然科学基金（No.61373077）；高等学校博士学科点专项科研基金（No.20110121110020）；国家部委基础科研计划项目；国家部委科技重点实验室基金资助。 （）
