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» Multiple Instance Boosting for Face Recognition in Videos
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CVPR
2006
IEEE
14 years 11 months ago
Locally Linear Models on Face Appearance Manifolds with Application to Dual-Subspace Based Classification
Recently, there has been a flurry of research on face recognition based on multiple images or shots from either a video sequence or an image set. This paper is also such an attemp...
Wei Fan, Dit-Yan Yeung
ICMCS
2009
IEEE
132views Multimedia» more  ICMCS 2009»
14 years 7 months ago
Video face recognition with graph-based semi-supervised learning
We consider the problem of classification of multiple observations of the same object, possibly under different transformations. We view this problem as a special case of semi-sup...
Effrosini Kokiopoulou, Pascal Frossard
AVSS
2006
IEEE
15 years 3 months ago
The Role of Motion Models in Super-Resolving Surveillance Video for Face Recognition
Although the use of super-resolution techniques has demonstrated the ability to improve face recognition accuracy when compared to traditional upsampling techniques, they are difļ...
Frank Lin, Clinton Fookes, Vinod Chandran, Sridha ...
SDM
2012
SIAM
252views Data Mining» more  SDM 2012»
12 years 12 months ago
Learning from Heterogeneous Sources via Gradient Boosting Consensus
Multiple data sources containing different types of features may be available for a given task. For instance, users’ profiles can be used to build recommendation systems. In a...
Xiaoxiao Shi, Jean-François Paiement, David...
CVPR
2005
IEEE
15 years 11 months ago
Online Learning of Probabilistic Appearance Manifolds for Video-Based Recognition and Tracking
This paper presents an online learning algorithm to construct from video sequences an image-based representation that is useful for recognition and tracking. For a class of object...
Kuang-Chih Lee, David J. Kriegman