TY - JOUR
T1 - An example-based face hallucination method for single-frame, low-resolution facial images
AU - Park, Jeong Seon
AU - Lee, Seong Whan
N1 - Funding Information:
Manuscript received May 4, 2007; revised May 1, 2008. Current version published September 10, 2008. This work was supported by the Ministry of Knowledge Economy, Korea, under the ITRC (Information Technology Research Center) support program supervised by the IITA (Institute of Information Technology Advancement) (IITA-2008-C1090-0801-0001) and the Intelligent Robotics Development Program, one of the 21st Century Frontier R&D Programs funded by the Ministry of Commerce, Industry and Energy of Korea. The associate editor coordinating the review of this manuscript and approving it for publication was Dr. Dimitri Van De Ville.
PY - 2008
Y1 - 2008
N2 - This paper proposes a face hallucination method for the reconstruction of high-resolution facial images from single-frame, low-resolution facial images. The proposed method has been derived from example-based hallucination methods and morphable face models. First, we propose a recursive error back-projection method to compensate for residual errors, and a region-based reconstruction method to preserve characteristics of local facial regions. Then, we define an extended morphable face model, in which an extended face is composed of the interpolated high-resolution face from a given low-resolution face, and its original high-resolution equivalent. Then, the extended face is separated into an extended shape and an extended texture. We performed various hallucination experiments using the MPI, XM2VTS, and KF databases, compared the reconstruction errors, structural similarity index, and recognition rates, and showed the effects of face detection errors and shape estimation errors. The encouraging results demonstrate that the proposed methods can improve the performance of face recognition systems. Especially the proposed method can enhance the resolution of single-frame, low-resolution facial images.
AB - This paper proposes a face hallucination method for the reconstruction of high-resolution facial images from single-frame, low-resolution facial images. The proposed method has been derived from example-based hallucination methods and morphable face models. First, we propose a recursive error back-projection method to compensate for residual errors, and a region-based reconstruction method to preserve characteristics of local facial regions. Then, we define an extended morphable face model, in which an extended face is composed of the interpolated high-resolution face from a given low-resolution face, and its original high-resolution equivalent. Then, the extended face is separated into an extended shape and an extended texture. We performed various hallucination experiments using the MPI, XM2VTS, and KF databases, compared the reconstruction errors, structural similarity index, and recognition rates, and showed the effects of face detection errors and shape estimation errors. The encouraging results demonstrate that the proposed methods can improve the performance of face recognition systems. Especially the proposed method can enhance the resolution of single-frame, low-resolution facial images.
KW - Error back-projection
KW - Example-based reconstruction
KW - Extended morphable face model
KW - Face hallucination
KW - Face recognition
KW - Region-based reconstruction
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U2 - 10.1109/TIP.2008.2001394
DO - 10.1109/TIP.2008.2001394
M3 - Article
C2 - 18784029
AN - SCOPUS:52549116762
VL - 17
SP - 1806
EP - 1816
JO - IEEE Transactions on Image Processing
JF - IEEE Transactions on Image Processing
SN - 1057-7149
IS - 10
ER -