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CVPR
2012
IEEE
11 years 6 months ago
On SIFTs and their scales
Scale invariant feature detectors often find stable scales in only a few image pixels. Consequently, methods for feature matching typically choose one of two extreme options: mat...
Tal Hassner, Viki Mayzels, Lihi Zelnik-Manor
CVPR
2012
IEEE
11 years 6 months ago
Generalized Multiview Analysis: A discriminative latent space
This paper presents a general multi-view feature extraction approach that we call Generalized Multiview Analysis or GMA. GMA has all the desirable properties required for cross-vi...
Abhishek Sharma, Abhishek Kumar, Hal Daumé ...
ICCV
2011
IEEE
12 years 3 months ago
A Linear Subspace Learning Approach via Sparse Coding
Linear subspace learning (LSL) is a popular approach to image recognition and it aims to reveal the essential features of high dimensional data, e.g., facial images, in a lower di...
Lei Zhang, Pengfei Zhu, Qinghu Hu, David Zhang
TIFS
2008
157views more  TIFS 2008»
13 years 3 months ago
Subspace Approximation of Face Recognition Algorithms: An Empirical Study
We present a theory for constructing linear subspace approximations to face-recognition algorithms and empirically demonstrate that a surprisingly diverse set of face-recognition a...
Pranab Mohanty, Sudeep Sarkar, Rangachar Kasturi, ...
IJCV
2007
163views more  IJCV 2007»
13 years 3 months ago
Appearance Sampling of Real Objects for Variable Illumination
Abstract. The appearance of an object greatly changes under different lighting conditions. Even so, previous studies have demonstrated that the appearance of an object under varyin...
Imari Sato, Takahiro Okabe, Yoichi Sato
PAMI
2006
208views more  PAMI 2006»
13 years 3 months ago
Combining Reconstructive and Discriminative Subspace Methods for Robust Classification and Regression by Subsampling
Linear subspace methods that provide sufficient reconstruction of the data, such as PCA, offer an efficient way of dealing with missing pixels, outliers, and occlusions that often ...
Sanja Fidler, Danijel Skocaj, Ales Leonardis
SOFSEM
2000
Springer
13 years 7 months ago
Computing the Dimension of Linear Subspaces
Abstract. Since its very beginning, linear algebra is a highly algorithmic subject. Let us just mention the famous Gau
Martin Ziegler, Vasco Brattka
COLT
2006
Springer
13 years 7 months ago
Online Tracking of Linear Subspaces
We address the problem of online de-noising a stream of input points. We assume that the clean data is embedded in a linear subspace. We present two online algorithms for tracking ...
Koby Crammer
ICCV
1999
IEEE
13 years 8 months ago
Multi-Frame Optical Flow Estimation using Subspace Constraints
We show that the set of all ow- elds in a sequence of frames imaging a rigid scene resides in a lowdimensional linear subspace. Based on this observation, we develop a method for ...
Michal Irani
COCO
2004
Springer
82views Algorithms» more  COCO 2004»
13 years 9 months ago
On the Power of Quantum Proofs
We study the power of quantum proofs, or more precisely, the power of Quantum MerlinArthur (QMA) protocols, in two well studied models of quantum computation: the black box model ...
Ran Raz, Amir Shpilka