K. Lee, J. Ho, and D. Kriegman. Nine points of light: Acquiring subspaces for face recognition under variable lighting. In Proc. of CVPR, pages 519--526, 2001. Home/Search Document Not in Database Summary Related Articles Check |
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Face Recognition Under Variable Lighting using Harmonic.. - Lei Zhang Dimitris (2003) (3 citations) (Correct)
....for each face are required. These images can be rendered from a 3D scan of the face or can be estimated by applying PCA to a number of images of the same subject under different illuminations [2] An effective approximation of this basis by 9 single light source images of a face was reported in [4]. The above mentioned methods need a number of images and or 3D scans of the subjects in the database, thus requiring specialized equipment and procedures for the capture of the training set, thus limiting their applicability. A promising earlier attempt by [5] used symmetric shape from shading ....
....pose with each subject having 45 face images taken under different directional light sources. Fig. 2 shows some of the images we used in our experiments. Subsets 1 2 3 4 Number of Images 70 120 120 140 Illumination 0 12 13 25 26 50 51 77 Table 1: The separation of the Yale Database Following [4], we group our data set in four subsets (Table 1) Each subset contains images illuminated from a specific range of directions. Subset 4 contains the extreme illu Figure 2. Some real images used in our experiments. mination conditions. Please refer to [4] for more information about this ....
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Kuang-Chih Lee, Jeffrey Ho and D.Kreigman, "Nine Points of Light: Acquiring Subspaces for Face Recognition under Variable Lighting," Proc. CVPR, (I:519-526), 2001 .
Recent Methods for Image-based Modeling and Rendering - Burschka, Cobzas, Dodds, al. (2003) (Correct)
....introduced. However, commonly the light will vary at least somewhat. In the past decade several published both empirical studies and theoretical motivations have shown that a low dimensional intensity subspace of dimension 5 9 is su#cient for representing the light variation of most natural scenes[30]. Hence we introduce nine additional freedoms in our variability model to allow for lighting. Complex scenes may require more, simple (convex lambertian) less) #T l = B 1 . B 9 ] y 1 . y 9 ] B l y l (57) 4.5 Estimating composite variability In textures sampled from a real scene using an ....
Kuang-Chih Lee, Je#rey Ho, and David Kriegman. Nine points of light: Acquiring subspaces for face recognition under variable lighting. In Computer Vision and Pattern Recognition, 2001. 79
Mitsubishi Electric Research Laboratories - Http Www Merl (2004) (Correct)
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K. Lee, J. Ho, and D. Kriegman. Nine points of light: Acquiring subspaces for face recognition under variable lighting. In Proc. of CVPR, pages 519--526, 2001.
A Bilinear Illumination Model for Robust Face Recognition - Lee, Moghaddam, Pfister.. (2005) (Correct)
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K. Lee, J. Ho, and D. Kriegman. Nine points of light: Acquiring subspaces for face recognition under variable lighting. In Proc. of Computer Vision & Pattern Recognition, volume 1, pages 519--526, 2001.
Mitsubishi Electric Research Laboratories - Http Www Merl (2005) (Correct)
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K. C. Lee, J. Ho, and D. Kriegman. Nine points of light: Acquiring subspaces for face recognition under variable lighting. In Proc. IEEE Conf. on Computer Vision & Pattern Recognition, pages 519--526, 2001.
Linear Projection Methods in Face Recognition under.. - Li, Ye, Kambhamettu (2004) (Correct)
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K. Lee, J. Ho, and D. Kriegman. Ninepoints of light: Acquiring subspaces for face recognition under variable lighting. In IEEE Conf. CVPR, pages 519--526, 2001.
Pose Invariant Face Recognition under Arbitrary Unknown.. - Lei Zhang And (Correct)
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K.C. Lee, J. Ho, and D.J. Kriegman. Nine points of light: Acquiring subspaces for face recognition under variable lighting. In CVPR, pages I:519--526, 2001.
Principal Component Analysis over Continuous Subspaces and.. - Levin, Shashua (2002) (1 citation) (Correct)
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K.C. Lee, J. Ho and D. Kriegman. Nine points of light: Acquiring subspaces for face recognition under variable lighting. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2001.
Finding Optimal Views for 3D Face Shape Modeling - Jinho Lee Baback (Correct)
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K. Lee, J. Ho, and D. Kriegman. Nine points of light: Acquiring subspaces for face recognition under variable lighting. In Proceedings of Computer Vision and Pattern Recognition, volume 1, pages 519--526, 2001.
Generic vs. Person Specific - Active Appearance Models (2004) (Correct)
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K.-C. Lee, L. Ho, and D. Kriegman. Nine points of light: Acquiring subspaces for face recognition under variable lighting. In IEEE CVPR, pages 519--526, 2001.
Finding Optimal Views for 3D Face Shape Modeling - Lee, Moghaddam, Pfister.. (2004) (Correct)
No context found.
K. Lee, J. Ho, and D. Kriegman. Nine points of light: Acquiring subspaces for face recognition under variable lighting. In Proc. of CVPR, pages 519--526, 2001.
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