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» Learning Mid-Level Features For Recognition
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ICPR
2006
IEEE
14 years 8 months ago
GMM-based SVM for face recognition
A new face recognition algorithm is presented. It supposes that a video sequence of a person is available both at enrollment and test time. During enrollment, a client Gaussian Mi...
Gérard Chollet, Hervé Bredin, Najim ...
ICB
2009
Springer
251views Biometrics» more  ICB 2009»
14 years 2 months ago
Heterogeneous Face Recognition from Local Structures of Normalized Appearance
Abstract. Heterogeneous face images come from different lighting conditions or different imaging devices, such as visible light (VIS) and near infrared (NIR) based. Because heter...
ShengCai Liao, Dong Yi, Zhen Lei, Rui Qin, Stan Z....
25
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ICCV
2005
IEEE
14 years 1 months ago
TemporalBoost for Event Recognition
This paper contributes a new boosting paradigm to achieve detection of events in video. Previous boosting paradigms in vision focus on single frame detection and do not scale to v...
Paul Smith, Niels da Vitoria Lobo, Mubarak Shah
ECML
2005
Springer
14 years 1 months ago
A Model Based Method for Automatic Facial Expression Recognition
Automatic facial expression recognition is a research topic with interesting applications in the field of human-computer interaction, psychology and product marketing. The classi...
Hans van Kuilenburg, Marco Wiering, Marten den Uyl
ICML
2009
IEEE
14 years 2 months ago
Sparse higher order conditional random fields for improved sequence labeling
In real sequence labeling tasks, statistics of many higher order features are not sufficient due to the training data sparseness, very few of them are useful. We describe Sparse H...
Xian Qian, Xiaoqian Jiang, Qi Zhang, Xuanjing Huan...