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CVPR
2005
IEEE
13 years 9 months ago
Jensen-Shannon Boosting Learning for Object Recognition
In this paper, we propose a novel learning method, called Jensen-Shannon Boosting (JSBoost) and demonstrate its application to object recognition. JSBoost incorporates Jensen-Shan...
Xiangsheng Huang, Stan Z. Li, Yangsheng Wang
CEC
2010
IEEE
13 years 4 months ago
An adaptive ensemble of fuzzy ARTMAP neural networks for video-based face classification
A key feature in population based optimization algorithms is the ability to explore a search space and make a decision based on multiple solutions. In this paper, an incremental le...
Jean-François Connolly, Eric Granger, Rober...
FGR
2011
IEEE
255views Biometrics» more  FGR 2011»
12 years 7 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
ICPR
2002
IEEE
14 years 4 months ago
Feature Selection for Pose Invariant Face Recognition
One of the major difficulties in face recognition systems is the in-depth pose variation problem. Most face recognition approaches assume that the pose of the face is known. In th...
Berk Gökberk, Ethem Alpaydin, Lale Akarun
ACCV
2010
Springer
12 years 10 months ago
Face Recognition with Decision Tree-Based Local Binary Patterns
Many state-of-the-art face recognition algorithms use image descriptors based on features known as Local Binary Patterns (LBPs). While many variations of LBP exist, so far none of ...
Daniel Maturana, Domingo Mery, Alvaro Soto