Pose-Encoded Spherical Harmonics for Face Recognition and Synthesis Using a Single Image
Face recognition under varying pose is a challenging problem, especially when illumination variations are also present. In this paper, we propose to address one of the most challenging scenarios in face recognition. That is, to identify a subject from a test image that is acquired under different po...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
SpringerOpen
2007-12-01
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| Series: | EURASIP Journal on Advances in Signal Processing |
| Online Access: | http://dx.doi.org/10.1155/2008/748483 |
| _version_ | 1819268539505180672 |
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| author | Rama Chellappa Wenyi Zhao Zhanfeng Yue |
| author_facet | Rama Chellappa Wenyi Zhao Zhanfeng Yue |
| author_sort | Rama Chellappa |
| collection | DOAJ |
| description | Face recognition under varying pose is a challenging problem, especially when illumination variations are also present. In this paper, we propose to address one of the most challenging scenarios in face recognition. That is, to identify a subject from a test image that is acquired under different pose and illumination condition from only one training sample (also known as a gallery image) of this subject in the database. For example, the test image could be semifrontal and illuminated by multiple lighting sources while the corresponding training image is frontal under a single lighting source. Under the assumption of Lambertian reflectance, the spherical harmonics representation has proved to be effective in modeling illumination variations for a fixed pose. In this paper, we extend the spherical harmonics representation to encode pose information. More specifically, we utilize the fact that 2D harmonic basis images at different poses are related by close-form linear transformations, and give a more convenient transformation matrix to be directly used for basis images. An immediate application is that we can easily synthesize a different view of a subject under arbitrary lighting conditions by changing the coefficients of the spherical harmonics representation. A more important result is an efficient face recognition method, based on the orthonormality of the linear transformations, for solving the above-mentioned challenging scenario. Thus, we directly project a nonfrontal view test image onto the space of frontal view harmonic basis images. The impact of some empirical factors due to the projection is embedded in a sparse warping matrix; for most cases, we show that the recognition performance does not deteriorate after warping the test image to the frontal view. Very good recognition results are obtained using this method for both synthetic and challenging real images. |
| first_indexed | 2024-12-23T21:34:40Z |
| format | Article |
| id | doaj.art-737788e22aa24945841c2a63c291c22a |
| institution | Directory Open Access Journal |
| issn | 1687-6172 |
| language | English |
| last_indexed | 2024-12-23T21:34:40Z |
| publishDate | 2007-12-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | EURASIP Journal on Advances in Signal Processing |
| spelling | doaj.art-737788e22aa24945841c2a63c291c22a2022-12-21T17:30:21ZengSpringerOpenEURASIP Journal on Advances in Signal Processing1687-61722007-12-01200810.1155/2008/748483Pose-Encoded Spherical Harmonics for Face Recognition and Synthesis Using a Single ImageRama ChellappaWenyi ZhaoZhanfeng YueFace recognition under varying pose is a challenging problem, especially when illumination variations are also present. In this paper, we propose to address one of the most challenging scenarios in face recognition. That is, to identify a subject from a test image that is acquired under different pose and illumination condition from only one training sample (also known as a gallery image) of this subject in the database. For example, the test image could be semifrontal and illuminated by multiple lighting sources while the corresponding training image is frontal under a single lighting source. Under the assumption of Lambertian reflectance, the spherical harmonics representation has proved to be effective in modeling illumination variations for a fixed pose. In this paper, we extend the spherical harmonics representation to encode pose information. More specifically, we utilize the fact that 2D harmonic basis images at different poses are related by close-form linear transformations, and give a more convenient transformation matrix to be directly used for basis images. An immediate application is that we can easily synthesize a different view of a subject under arbitrary lighting conditions by changing the coefficients of the spherical harmonics representation. A more important result is an efficient face recognition method, based on the orthonormality of the linear transformations, for solving the above-mentioned challenging scenario. Thus, we directly project a nonfrontal view test image onto the space of frontal view harmonic basis images. The impact of some empirical factors due to the projection is embedded in a sparse warping matrix; for most cases, we show that the recognition performance does not deteriorate after warping the test image to the frontal view. Very good recognition results are obtained using this method for both synthetic and challenging real images.http://dx.doi.org/10.1155/2008/748483 |
| spellingShingle | Rama Chellappa Wenyi Zhao Zhanfeng Yue Pose-Encoded Spherical Harmonics for Face Recognition and Synthesis Using a Single Image EURASIP Journal on Advances in Signal Processing |
| title | Pose-Encoded Spherical Harmonics for Face Recognition and Synthesis Using a Single Image |
| title_full | Pose-Encoded Spherical Harmonics for Face Recognition and Synthesis Using a Single Image |
| title_fullStr | Pose-Encoded Spherical Harmonics for Face Recognition and Synthesis Using a Single Image |
| title_full_unstemmed | Pose-Encoded Spherical Harmonics for Face Recognition and Synthesis Using a Single Image |
| title_short | Pose-Encoded Spherical Harmonics for Face Recognition and Synthesis Using a Single Image |
| title_sort | pose encoded spherical harmonics for face recognition and synthesis using a single image |
| url | http://dx.doi.org/10.1155/2008/748483 |
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