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» Unsupervised Learning of Invariant Features Using Video
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CVPR
2008
IEEE
14 years 9 months ago
Parameterized Kernel Principal Component Analysis: Theory and applications to supervised and unsupervised image alignment
Parameterized Appearance Models (PAMs) (e.g. eigentracking, active appearance models, morphable models) use Principal Component Analysis (PCA) to model the shape and appearance of...
Fernando De la Torre, Minh Hoai Nguyen
CIVR
2010
Springer
199views Image Analysis» more  CIVR 2010»
14 years 13 days ago
Unsupervised multi-feature tag relevance learning for social image retrieval
Interpreting the relevance of a user-contributed tag with respect to the visual content of an image is an emerging problem in social image retrieval. In the literature this proble...
Xirong Li, Cees G. M. Snoek, Marcel Worring
ICIP
2004
IEEE
14 years 9 months ago
New features for affine-invariant shape classification
An object seen from different viewpoints results in differently deformed images. Affine-invariant shape classification must classify correctly the object, disregarding its viewpoi...
Carlos Ramon Pantaleon Dionisio, Hae Yong Kim
AAAI
2007
13 years 10 months ago
Detection of Multiple Deformable Objects using PCA-SIFT
In this paper, we address the problem of identifying and localizing multiple instances of highly deformable objects in real-time video data. We present an approach which uses PCA-...
Stefan Zickler, Alexei A. Efros
ICIP
2009
IEEE
13 years 5 months ago
View-invariant action recognition using cross ratios across frames
We present a new method of computing invariants in videos captured from different views to achieve view-invariant action recognition. To avoid the constraints of collinearity or c...
Yeyin Zhang, Kaiqi Huang, Yongzhen Huang, Tieniu T...