TY - GEN
T1 - Resolution enhancement of facial image based on topdown learning
AU - Park, Jeong Seon
AU - Lee, Seong Whan
N1 - Funding Information:
Face Recognition, low-resolution, face reconstruction, mor-phable face model ∗This research was supported by Creative Research Initiatives of the Ministry of Science and Technology, Korea.
Publisher Copyright:
Copyright 2003 ACM.
Copyright:
Copyright 2017 Elsevier B.V., All rights reserved.
PY - 2003/11/2
Y1 - 2003/11/2
N2 - This paper proposes a new method of synthesizing a highresolution facial image from a low-resolution facial image based on top-down learning. A face is represented by a linear combination of prototypes of shape and texture. With the shape and texture information about the pixels in a given low-resolution facial image, we can estimate optimal coefficients for a linear combination of prototypes of shape and those of texture by solving least square minimization. Then high-resolution facial image can be synthesized by using the optimal coefficients for linear combination of the high-resolution prototypes. The encouraging results of the proposed method show that our method can be used to increase the performance of the face recognition by applying our method to enhance the low-resolution facial images captured at surveillance systems.
AB - This paper proposes a new method of synthesizing a highresolution facial image from a low-resolution facial image based on top-down learning. A face is represented by a linear combination of prototypes of shape and texture. With the shape and texture information about the pixels in a given low-resolution facial image, we can estimate optimal coefficients for a linear combination of prototypes of shape and those of texture by solving least square minimization. Then high-resolution facial image can be synthesized by using the optimal coefficients for linear combination of the high-resolution prototypes. The encouraging results of the proposed method show that our method can be used to increase the performance of the face recognition by applying our method to enhance the low-resolution facial images captured at surveillance systems.
KW - Face recognition
KW - Face reconstruction
KW - Low-resolution
KW - Morphable face model
UR - http://www.scopus.com/inward/record.url?scp=84968768275&partnerID=8YFLogxK
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U2 - 10.1145/982452.982460
DO - 10.1145/982452.982460
M3 - Conference contribution
AN - SCOPUS:84968768275
T3 - 1st ACM SIGMM International Workshop on Video Surveillance, IWVS 2003
SP - 59
EP - 64
BT - 1st ACM SIGMM International Workshop on Video Surveillance, IWVS 2003
PB - Association for Computing Machinery, Inc
T2 - 1st ACM SIGMM International Workshop on Video Surveillance, IWVS 2003
Y2 - 2 November 2003 through 8 November 2003
ER -