W. Zhao and R. Chellappa. Robust face recognition using symmetric shape-from-shading. Technical Report CAR-TR-919, Center for automation research, University of Maryland, 1999. Home/Search Document Details and Download
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In Proceedings of Workshop on Models versus Exemplars in.. - Combining Models And (2001) (Correct)
....The second approach attempts to normalize away the variation, either by clever image transformations or by synthesizing a new image (from the given task image) in some canonical or prototypical form. Recognition is then performed using this canonical form. Examples of this approach include [23, 24]. In [23] for instance, the task image under arbitrary illumination is re rendered under frontal illumination, and then compared against other frontally illuminated prototypes. The third approach of variation modelling is selfexplanatory: the idea is to learn, in some suitable subspace, the ....
....approach attempts to normalize away the variation, either by clever image transformations or by synthesizing a new image (from the given task image) in some canonical or prototypical form. Recognition is then performed using this canonical form. Examples of this approach include [23, 24] In [23], for instance, the task image under arbitrary illumination is re rendered under frontal illumination, and then compared against other frontally illuminated prototypes. The third approach of variation modelling is selfexplanatory: the idea is to learn, in some suitable subspace, the extent of the ....
[Article contains additional citation context not shown here]
W. Zhao and R. Chellappa. Robust Face Recognition using Symmetric Shape-from-Shading. Technical Report CARTR -919, 1999.
Combining Models and Exemplars for Face Recognition: An.. - Sim, Kanade (2001) (1 citation) (Correct)
....The second approach attempts to normalize away the variation, either by clever image transformations or by synthesizing a new image (from the given task image) in some canonical or prototypical form. Recognition is then performed using this canonical form. Examples of this approach include [23, 24]. In [23] for instance, the task image under arbitrary illumination is re rendered under frontal illumination, and then compared against other frontally illuminated prototypes. The third approach of variation modelling is selfexplanatory: the idea is to learn, in some suitable subspace, the ....
....approach attempts to normalize away the variation, either by clever image transformations or by synthesizing a new image (from the given task image) in some canonical or prototypical form. Recognition is then performed using this canonical form. Examples of this approach include [23, 24] In [23], for instance, the task image under arbitrary illumination is re rendered under frontal illumination, and then compared against other frontally illuminated prototypes. The third approach of variation modelling is selfexplanatory: the idea is to learn, in some suitable subspace, the extent of the ....
[Article contains additional citation context not shown here]
W. Zhao and R. Chellappa. Robust Face Recognition using Symmetric Shape-from-Shading. Technical Report CARTR -919,
Face Recognition: A Literature Survey - Zhao, Chellappa, Rosenfeld.. (2000) (55 citations) Self-citation (Zhao Chellappa) (Correct)
....a change in lighting. The changes induced by illumination are often larger than the differences between individuals, causing systems based on comparing images to misclassify input images. This was experimentally observed in [181] using a dataset of 25 individuals, and was theoretically proved in [182] for systems based on eigenface projection. Figure 14: The same face appears differently under different illuminations. The illumination problem is quite difficult and has received consistent attention in the image understanding literature. In the case of face recognition, many approaches to ....
....ill posed SFS problem is thereby transformed into a parametric problem, but constant albedo is still assumed. This assumption does not hold for most real face images and it is one of the reasons why most SFS algorithms fail on real face images. To overcome the constant albedo issue, the authors of [68, 182] proposed using a varying albedo reflectance model. They first proposed a new SFS scheme, symmetric SFS. Unlike existing SFS algorithms, Symmetric SFS theoretically allows pointwise 3D information about a symmetric object, represented by the shape gradients (p; q) to be uniquely recovered from a ....
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W. Zhao and R. Chellappa, "Robust Face Recognition using Symmetric Shapefrom -Shading," Technical Report CAR-TR-919, Center for Automation Research, University of Maryland, 1999.
A Reliable Descriptor for Face Objects in Visual Content - Zhao, Bhat, Wang.. Self-citation (Zhao Chellappa) (Correct)
.... illumination variation, currently a face mask and a heuristic approach based on face symmetry are applied to the input images before they are fed into the system [8] Recently some systematic approaches have been suggested for dealing with illumination variation for face recognition ( for example, [12], 13] we intend to look at the problem closer. Several important issues have yet to be dealt with, for instance, coding of the descriptor in MPEG 7 streams. First, how should the linear discriminant matrix be transmitted Clearly, it is inefficient to transmit the matrix with every face ....
W. Zhao and R. Chellappa, "Robust face recognition using symmetric shape-fromshading, " University of Maryland, Center for Automation Research, Technical Report CARTR -919, 1999.
SFS Based View Synthesis for Robust Face Recognition - Zhao, Chellappa (2000) (7 citations) Self-citation (Zhao Chellappa) (Correct)
....is enough. However when the lighting model is included, the same point [x; y] x 0 ; y 0 ] in the face appears differently under different poses. And pure image warping does not resolve the reflectance difference But the interesting thing is that if we can assume frontal face symmetry as in [30], then we have the following proposition Proposition 1 The optimal discriminant mapping W learned from front view face images is also optimal for distinguishing among rotated face images provided that ffl all the eigenimages are symmetric, which is a direct result of training on ....
....This is the most difficult problem where we need to handle both pose and illumination variations. The technique used in computer graphics to model 3D face is too complicated for the task of face recognition with large database. In theory, we can also apply SFS or a recent work on symmetric SFS [30] to recover the complete 3D shape. However to be more practical, we propose using a simple 3D model to by pass this 2Dto 3D process. This technique has been successfully applied in [30] to address pure illumination problem with pose fixed. 4.2.1 Virtual View Synthesis for Recognition The basic ....
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W. Zhao, and R. Chellappa, "Robust Face Recognition using Symmetric Shape-from-Shading," Center for Automation Research, University of Maryland, College Park, Technical Report CARTR -919, 1999.
Decision Fusion in Identity Verification using Facial Images - Czyz (2003) (Correct)
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W. Zhao and R. Chellappa. Robust face recognition using symmetric shape-from-shading. Technical Report CAR-TR-919, Center for automation research, University of Maryland, 1999.
Face Recognition Across Pose and Illumination - Ralph Gross Simon (2004) (Correct)
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W. Zhao and R. Chellappa. Robust face recognition using symmetric shapefrom -shading. Technical report, Center for Automation Research, University of Maryland, 1999.
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