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» Robust Principal Component Analysis for Computer Vision
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APWEB
2005
Springer
14 years 1 months ago
An Incremental Subspace Learning Algorithm to Categorize Large Scale Text Data
The dramatic growth in the number and size of on-line information sources has fueled increasing research interest in the incremental subspace learning problem. In this paper, we pr...
Jun Yan, QianSheng Cheng, Qiang Yang, Benyu Zhang
ECCV
2002
Springer
14 years 9 months ago
Diffuse-Specular Separation and Depth Recovery from Image Sequences
Specular reflections present difficulties for many areas of computer vision such as stereo and segmentation. To separate specular and diffuse reflection components, previous approa...
Stephen Lin, Yuanzhen Li, Sing Bing Kang, Xin Tong...
BMVC
2000
13 years 9 months ago
Probabilistic PCA and ICA Subspace Mixture Models for Image Segmentation
High-dimensional data, such as images represented as points in the space spanned by their pixel values, can often be described in a significantly smaller number of dimensions than...
Dick de Ridder, Josef Kittler, Robert P. W. Duin
ICCV
2005
IEEE
14 years 9 months ago
Consistent Surface Color for Texturing Large Objects in Outdoor Scenes
Color appearance of an object is significantly influenced by the color of the illumination. When the illumination color changes, the color appearance of the object will change acc...
Rei Kawakami, Katsushi Ikeuchi, Robby T. Tan
ICMCS
2007
IEEE
223views Multimedia» more  ICMCS 2007»
14 years 2 months ago
An Effective Local Invariant Descriptor Combining Luminance and Color Information
Extraction of stable local invariant features is very important in many computer vision applications, such as image matching, object recognition and image retrieval. Most existing...
Dong Zhang, Weiqiang Wang, Wen Gao, Shuqiang Jiang