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» Forecasting high-dimensional data
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ICCV
2005
IEEE
15 years 3 months ago
Appearance Manifold of Facial Expression
This paper investigates the appearance manifold of facial expression: embedding image sequences of facial expression from the high dimensional appearance feature space to a low dim...
Caifeng Shan, Shaogang Gong, Peter W. McOwan
ICTAI
2005
IEEE
15 years 3 months ago
Latent Process Model for Manifold Learning
In this paper, we propose a novel stochastic framework for unsupervised manifold learning. The latent variables are introduced, and the latent processes are assumed to characteriz...
Gang Wang, Weifeng Su, Xiangye Xiao, Frederick H. ...
ICCSA
2003
Springer
15 years 3 months ago
Efficient Speaker Identification Based on Robust VQ-PCA
Abstract. In this paper, an efficient speaker identification based on robust vector quantization principal component analysis (VQ-PCA) is proposed to solve the problems from outlie...
Younjeong Lee, Joohun Lee, Ki Yong Lee
IDEAL
2003
Springer
15 years 3 months ago
GMM Based on Local Fuzzy PCA for Speaker Identification
To reduce the high dimensionality required for training of feature vectors in speaker identification, we propose an efficient GMM based on local PCA with Fuzzy clustering. The prop...
JongJoo Lee, JaeYeol Rheem, Ki Yong Lee
ICPR
2010
IEEE
15 years 2 months ago
On the Dimensionality Reduction for Sparse Representation Based Face Recognition
Face recognition (FR) is an active yet challenging topic in computer vision applications. As a powerful tool to represent high dimensional data, recently sparse representation bas...
Lei Zhang, Meng Yang, Zhizhao Feng, David Zhang