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CVPR
2003
IEEE
16 years 6 months ago
Object Class Recognition by Unsupervised Scale-Invariant Learning
We present a method to learn and recognize object class models from unlabeled and unsegmented cluttered scenes in a scale invariant manner. Objects are modeled as flexible constel...
Robert Fergus, Pietro Perona, Andrew Zisserman
CVPR
2008
IEEE
16 years 6 months ago
Latent topic random fields: Learning using a taxonomy of labels
An important problem in image labeling concerns learning with images labeled at varying levels of specificity. We propose an approach that can incorporate images with labels drawn...
Xuming He, Richard S. Zemel
ICPR
2004
IEEE
16 years 5 months ago
Hierarchical Object Indexing and Sequential Learning
This work is about scene interpretation in the sense of detecting and localizing instances from multiple object classes. We concentrate on object indexing: generate an over-comple...
Donald Geman, Xiaodong Fan
ICPR
2002
IEEE
16 years 5 months ago
Unsupervised Learning Using Locally Linear Embedding: Experiments with Face Pose Analysis
This paper considers a recently proposed method for unsupervised learning and dimensionality reduction, locally linear embedding (LLE). LLE computes a compact representation of hi...
Abdenour Hadid, Matti Pietikäinen, Olga Kouro...
ICIP
2009
IEEE
16 years 5 months ago
Learning Large Margin Likelihoods For Realtime Head Pose Tracking
We consider the problem of head tracking and pose estimation in realtime from low resolution images. Tracking and pose recognition are treated as two coupled problems in a probabi...