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» Learning a Sparse Representation for Object Detection
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BMVC
1998
13 years 6 months ago
ORASSYLL: Object Recognition with Autonomously Learned and Sparse Symbolic Representations Based on Local Line Detectors
We introduce an object recognition system in which objects are represented as a sparse and spatially organized set of local (bent) line segments. The line segments correspond to b...
Norbert Krüger, Niklas Lüdtke
WACV
2012
IEEE
12 years 24 days ago
Online discriminative object tracking with local sparse representation
We propose an online algorithm based on local sparse representation for robust object tracking. Local image patches of a target object are represented by their sparse codes with a...
Qing Wang, Feng Chen, Wenli Xu, Ming-Hsuan Yang
IJON
2008
168views more  IJON 2008»
13 years 5 months ago
Spatial relationship representation for visual object searching
Image representation has been a key issue in vision research for many years. In order to represent various local image patterns or objects effectively, it is important to study th...
Jun Miao, Lijuan Duan, Laiyun Qing, Wen Gao, Xilin...
FGR
2011
IEEE
288views Biometrics» more  FGR 2011»
12 years 8 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 ...
ICML
2010
IEEE
13 years 6 months ago
Submodular Dictionary Selection for Sparse Representation
We develop an efficient learning framework to construct signal dictionaries for sparse representation by selecting the dictionary columns from multiple candidate bases. By sparse,...
Andreas Krause, Volkan Cevher