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ICML
2006
IEEE
15 years 10 months ago
Null space versus orthogonal linear discriminant analysis
Dimensionality reduction is an important pre-processing step for many applications. Linear Discriminant Analysis (LDA) is one of the well known methods for supervised dimensionali...
Jieping Ye, Tao Xiong
CIVR
2006
Springer
121views Image Analysis» more  CIVR 2006»
15 years 1 months ago
Finding Faces in Gray Scale Images Using Locally Linear Embeddings
The problem of face detection remains challenging because faces are non-rigid objects that have a high degree of variability with respect to head rotation, illumination, facial exp...
Samuel Kadoury, Martin D. Levine
VLDB
2007
ACM
197views Database» more  VLDB 2007»
15 years 9 months ago
Indexable PLA for Efficient Similarity Search
Similarity-based search over time-series databases has been a hot research topic for a long history, which is widely used in many applications, including multimedia retrieval, dat...
Qiuxia Chen, Lei Chen 0002, Xiang Lian, Yunhao Liu...
NIPS
2008
14 years 11 months ago
Dimensionality Reduction for Data in Multiple Feature Representations
In solving complex visual learning tasks, adopting multiple descriptors to more precisely characterize the data has been a feasible way for improving performance. These representa...
Yen-Yu Lin, Tyng-Luh Liu, Chiou-Shann Fuh
FGR
2000
IEEE
181views Biometrics» more  FGR 2000»
15 years 2 months ago
Face Detection Using Mixtures of Linear Subspaces
We present two methods using mixtures of linear subspaces for face detection in gray level images. One method uses a mixture of factor analyzers to concurrently perform clustering...
Ming-Hsuan Yang, Narendra Ahuja, David J. Kriegman