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» Adaptation of SIFT Features for Robust Face Recognition
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ACCV
2006
Springer
13 years 11 months ago
Biologically Motivated Perceptual Feature: Generalized Robust Invariant Feature
Abstract. In this paper, we present a new, biologically inspired perceptual feature to solve the selectivity and invariance issue in object recognition. Based on the recent findin...
Sungho Kim, In-So Kweon
PAMI
2007
262views more  PAMI 2007»
13 years 4 months ago
An Efficient Multimodal 2D-3D Hybrid Approach to Automatic Face Recognition
—We present a fully automatic face recognition algorithm and demonstrate its performance on the FRGC v2.0 data. Our algorithm is multimodal (2D and 3D) and performs hybrid (featu...
Ajmal S. Mian, Mohammed Bennamoun, Robyn A. Owens
FGR
2011
IEEE
255views Biometrics» more  FGR 2011»
12 years 9 months ago
Beyond simple features: A large-scale feature search approach to unconstrained face recognition
— Many modern computer vision algorithms are built atop of a set of low-level feature operators (such as SIFT [1], [2]; HOG [3], [4]; or LBP [5], [6]) that transform raw pixel va...
David D. Cox, Nicolas Pinto
ACIVS
2006
Springer
13 years 9 months ago
Context-Based Scene Recognition Using Bayesian Networks with Scale-Invariant Feature Transform
Scene understanding is an important problem in intelligent robotics. Since visual information is uncertain due to several reasons, we need a novel method that has robustness to the...
Seung-Bin Im, Sung-Bae Cho
ICPR
2008
IEEE
13 years 12 months ago
A new hierarchical approach in robust real-time image feature detection and matching
Object recognition forms a ubiquitous problem in digital image processing. The detection of robust image features of high distinctiveness is one important key in this regard. We p...
Matthias Langer, Klaus-Dieter Kuhnert