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» Learning Shift-Invariant Sparse Representation of Actions
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CVPR
2010
IEEE
14 years 6 months ago
Learning Shift-Invariant Sparse Representation of Actions
A central problem in the analysis of motion capture (Mo- Cap) data is how to decompose motion sequences into primitives. Ideally, a description in terms of primitives should fac...
Yi Li
FGR
2011
IEEE
288views Biometrics» more  FGR 2011»
13 years 1 months ago
Facial action unit recognition with sparse representation
This paper presents a novel framework for recognition of facial action unit (AU) combinations by viewing the classification as a sparse representation problem. Based on this framew...
Mohammad H. Mahoor, Mu Zhou, Kevin L. Veon, Seyed ...
ICCV
2011
IEEE
12 years 10 months ago
Sparse Dictionary-based Representation and Recognition of Action Attributes
We present an approach for dictionary learning of action attributes via information maximization. We unify the class distribution and appearance information into an objective func...
Qiang Qiu, Zhuolin Jiang, Rama Chellappa

Publication
200views
12 years 5 months ago
Learning Tags from Unsegmented Videos of Multiple Human Actions
Providing methods to support semantic interaction with growing volumes of video data is an increasingly important challenge for data mining. To this end, there has been some succes...
Timothy Hospedales, Shaogang Gong, Tao Xiang
CVPR
2012
IEEE
12 years 12 days ago
Submodular dictionary learning for sparse coding
A greedy-based approach to learn a compact and discriminative dictionary for sparse representation is presented. We propose an objective function consisting of two components: ent...
Zhuolin Jiang, Guangxiao Zhang, Larry S. Davis