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예제학습 방법에 기반한 저해상도 얼굴 영상 복원Face Hallucination based on Example-Learning

Other Titles
Face Hallucination based on Example-Learning
Authors
이준태김재협문영식
Issue Date
Oct-2008
Publisher
대한전기학회
Citation
대한전자공학회 2008 CICS 정보 및 제어 학술대회 논문집, pp.292 - 293
Indexed
OTHER
Journal Title
대한전자공학회 2008 CICS 정보 및 제어 학술대회 논문집
Start Page
292
End Page
293
URI
https://scholarworks.bwise.kr/erica/handle/2021.sw.erica/42124
Abstract
In this paper, we propose a face hallucination method based on example-learning. The traditional approach based on example-learning requires alignment of face images. In the proposed method, facial images are segmented into patches and the weights are computed to represent input low resolution facial images into weighted sum of low resolution example images. High resolution facial images arc hallucinated by combining the weight vectors with the corresponding high resolution patches in the training set. Experimental results show that the proposed method produces more reliable results of face hallucination than the ones by the traditional approach based on example-learning.
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COLLEGE OF COMPUTING > SCHOOL OF COMPUTER SCIENCE > 1. Journal Articles

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