中国科学院机构知识库网格
Chinese Academy of Sciences Institutional Repositories Grid
Online learning a high-quality dictionary and classifier jointly for multitask object tracking

文献类型:期刊论文

作者Fan BJ(范保杰); Gao, Hao; Cong Y(丛杨); Du YK(杜英魁); Tang YD(唐延东)
刊名IEEE Multimedia
出版日期2014
卷号21期号:4页码:56-66
关键词Encoding (symbols) Learning systems Target tracking
ISSN号1070986X
产权排序2
通讯作者范保杰
中文摘要Object tracking in a particle filter framework is formulated as a binary classification problem. The method exploits a priori information from training data to jointly learn a discriminative dictionary and optimal classifier online.
WOS标题词Science & Technology ; Technology
类目[WOS]Computer Science, Hardware & Architecture ; Computer Science, Information Systems ; Computer Science, Software Engineering ; Computer Science, Theory & Methods
研究领域[WOS]Computer Science
关键词[WOS]SPARSE REPRESENTATION ; VISUAL TRACKING ; K-SVD ; RECOGNITION ; FEATURES ; MODEL
收录类别SCI ; EI
语种英语
WOS记录号WOS:000344995000008
公开日期2014-11-29
源URL[http://ir.sia.cn/handle/173321/15283]  
专题沈阳自动化研究所_机器人学研究室
推荐引用方式
GB/T 7714
Fan BJ,Gao, Hao,Cong Y,et al. Online learning a high-quality dictionary and classifier jointly for multitask object tracking[J]. IEEE Multimedia,2014,21(4):56-66.
APA Fan BJ,Gao, Hao,Cong Y,Du YK,&Tang YD.(2014).Online learning a high-quality dictionary and classifier jointly for multitask object tracking.IEEE Multimedia,21(4),56-66.
MLA Fan BJ,et al."Online learning a high-quality dictionary and classifier jointly for multitask object tracking".IEEE Multimedia 21.4(2014):56-66.

入库方式: OAI收割

来源:沈阳自动化研究所

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