Online State-Based Structured SVM Combined With Incremental PCA for Robust Visual Tracking

doi:10.1109/TCYB.2014.2363078

CASIA OpenIR > 中国科学院工业视觉智能装备工程实验室 > 精密感知与控制

	Online State-Based Structured SVM Combined With Incremental PCA for Robust Visual Tracking
	Yin, Yingjie; Xu, De; Wang, Xingang; Bai, Mingran
发表期刊	IEEE TRANSACTIONS ON CYBERNETICS
	2015-09-01
卷号	45 期号:9 页码:1988-2000
文章类型	Article
摘要	In this paper, we propose a robust state-based structured support vector machine (SVM) tracking algorithm combined with incremental principal component analysis (PCA). Different from the current structured SVM for tracking, our method directly learns and predicts the object's states and not the 2-D translation transformation during tracking. We define the object's virtual state to combine the state-based structured SVM and incremental PCA. The virtual state is considered as the most confident state of the object in every frame. The incremental PCA is used to update the virtual feature vector corresponding to the virtual state and the principal subspace of the object's feature vectors. In order to improve the accuracy of the prediction, all the feature vectors are projected onto the principal subspace in the learning and prediction process of the state-based structured SVM. Experimental results on several challenging video sequences validate the effectiveness and robustness of our approach.
关键词	Incremental Pca Object Tracking State Space Structured Svm
WOS标题词	Science & Technology ; Technology
DOI	10.1109/TCYB.2014.2363078
关键词[WOS]	SPARSE APPEARANCE MODEL ; VECTOR MACHINE ; REPRESENTATION ; SELECTION
收录类别	SCI
语种	英语
WOS研究方向	Computer Science
WOS类目	Computer Science, Artificial Intelligence ; Computer Science, Cybernetics
WOS记录号	WOS:000360019000023
引用统计	被引频次：39[WOS] [WOS记录] [WOS相关记录]
文献类型	期刊论文
条目标识符	http://ir.ia.ac.cn/handle/173211/8956
专题	中国科学院工业视觉智能装备工程实验室_精密感知与控制
作者单位	Chinese Acad Sci, Inst Automat, Res Ctr Precis Sensing & Control, Beijing 100190, Peoples R China
第一作者单位	精密感知与控制研究中心
推荐引用方式 GB/T 7714	Yin, Yingjie,Xu, De,Wang, Xingang,et al. Online State-Based Structured SVM Combined With Incremental PCA for Robust Visual Tracking[J]. IEEE TRANSACTIONS ON CYBERNETICS,2015,45(9):1988-2000.
APA	Yin, Yingjie,Xu, De,Wang, Xingang,&Bai, Mingran.(2015).Online State-Based Structured SVM Combined With Incremental PCA for Robust Visual Tracking.IEEE TRANSACTIONS ON CYBERNETICS,45(9),1988-2000.
MLA	Yin, Yingjie,et al."Online State-Based Structured SVM Combined With Incremental PCA for Robust Visual Tracking".IEEE TRANSACTIONS ON CYBERNETICS 45.9(2015):1988-2000.

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