The DOI matches its Crossref record; 22 of the 22 references it cites were found in a registry or an index.
Hallucinating Face by Eigentransformation
Abstract
In video surveillance, the faces of interest are often of small size. Image resolution is an important factor affecting face recognition by human and computer. In this paper, we propose a new face hallucination method using eigentransformation. Different from most of the proposed methods based on probabilistic models, this method views hallucination as a transformation between different image styles. We use Principal Component Analysis (PCA) to fit the input face image as a linear combination of the low-resolution face images in the training set. The high-resolution image is rendered by replacing the low-resolution training images with high-resolution ones, while retaining the same combination coefficients. Experiments show that the hallucinated face images are not only very helpful for recognition by humans, but also make the automatic recognition procedure easier, since they emphasize the face difference by adding more high-frequency details.
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Limits on super-resolution and how to break them
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Cited by
Image super-resolution: the techniques, applications, and future
Yue, L., Shen, H., Li, J., Yuan, Q., Zhang, H., & Zhang, L. (2016) · Signal Processing · doi:10.1016/j.sigpro.2016.05.002 · Cited by 554
Wavelet-SRNet: A Wavelet-Based CNN for Multi-scale Face Super Resolution
Huang, H., He, R., Sun, Z., & Tan, T. (2017) · 2017 IEEE International Conference on Computer Vision (ICCV) · doi:10.1109/iccv.2017.187 · Cited by 518
Face Recognition at a Distance
Peng, Y. (2018) · doi:10.3990/1.9789036547116
Metadata
- Authors
- Wang, X., & Tang, X.
- Venue
- IEEE Transactions on Systems, Man and Cybernetics, Part C (Applications and Reviews)
- Published
- 2005-08
- Volume
- 35
- Issue
- 3
- Pages
- 425-434
- ISSN
- 1094-6977 (ISSN-L)
- OpenAlex
- W2141631520
- Cited by
- 482
- References
- 22
- FWCI
- 13.56
- Type
- journal article
- Language
- en
- Open access
- closed
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