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» On the Dimensionality of Face Space
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CVPR
2008
IEEE
16 years 8 months ago
Large-scale manifold learning
This paper examines the problem of extracting lowdimensional manifold structure given millions of highdimensional face images. Specifically, we address the computational challenge...
Ameet Talwalkar, Sanjiv Kumar, Henry A. Rowley
BMVC
2000
15 years 7 months ago
Recognising the Dynamics of Faces across Multiple Views
We present an integrated framework for dynamic face detection and recognition, where head pose is estimated using Support Vector Regression, face detection is performed by Support...
Yongmin Li, Shaogang Gong, Heather M. Liddell
SDM
2007
SIAM
126views Data Mining» more  SDM 2007»
15 years 7 months ago
Nonlinear Dimensionality Reduction using Approximate Nearest Neighbors
Nonlinear dimensionality reduction methods often rely on the nearest-neighbors graph to extract low-dimensional embeddings that reliably capture the underlying structure of high-d...
Erion Plaku, Lydia E. Kavraki
SDM
2007
SIAM
108views Data Mining» more  SDM 2007»
15 years 7 months ago
Semi-Supervised Dimensionality Reduction
Dimensionality reduction is among the keys in mining highdimensional data. This paper studies semi-supervised dimensionality reduction. In this setting, besides abundant unlabeled...
Daoqiang Zhang, Zhi-Hua Zhou, Songcan Chen
SOCO
2008
Springer
15 years 6 months ago
A particular Gaussian mixture model for clustering and its application to image retrieval
We introduce a new method for data clustering based on a particular Gaussian mixture model (GMM). Each cluster of data, modeled as a GMM into an input space, is interpreted as a hy...
Hichem Sahbi