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» Learning Image Components for Object Recognition
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ICCV
2003
IEEE
16 years 4 months ago
Appearance Sampling for Obtaining A Set of Basis Images for Variable Illumination
Previous studies have demonstrated that the appearance of an object under varying illumination conditions can be represented by a low-dimensional linear subspace. A set of basis i...
Imari Sato, Takahiro Okabe, Yoichi Sato, Katsushi ...
CVPR
2007
IEEE
16 years 4 months ago
Towards Scalable Representations of Object Categories: Learning a Hierarchy of Parts
This paper proposes a novel approach to constructing a hierarchical representation of visual input that aims to enable recognition and detection of a large number of object catego...
Sanja Fidler, Ales Leonardis
ICPR
2000
IEEE
16 years 4 months ago
Growing Gaussian Mixture Models for Pose Invariant Face Recognition
A major challenge for face recognition algorithms lies in the variance faces undergo while changing pose. This problem is typically addressed by building view dependent models bas...
Ralph Gross, Jie Yang, Alex Waibel
NIPS
2001
15 years 4 months ago
Probabilistic principles in unsupervised learning of visual structure: human data and a model
To find out how the representations of structured visual objects depend on the co-occurrence statistics of their constituents, we exposed subjects to a set of composite images wit...
Shimon Edelman, Benjamin P. Hiles, Hwajin Yang, Na...
CVPR
2005
IEEE
16 years 4 months ago
Identifying Semantically Equivalent Object Fragments
We describe a novel technique for identifying semantically equivalent parts in images belonging to the same object class, (e.g. eyes, license plates, aircraft wings etc.). The vis...
Boris Epshtein, Shimon Ullman