Glasses removal from facial image using recursive error compensation

Jeong Seon Park; You Hwa Oh; Sang Chul Ahn; Seong Whan Lee

doi:10.1109/TPAMI.2005.103

Glasses removal from facial image using recursive error compensation

Jeong Seon Park, You Hwa Oh, Sang Chul Ahn, Seong Whan Lee

Department of Artificial Intelligence

Research output: Contribution to journal › Article › peer-review

122 Citations (Scopus)

Abstract

In this paper, we propose a new method of removing glasses from a human frontal facial image. We first detect the regions occluded by the glasses and generate a natural looking facial image without glasses by recursive error compensation using PCA reconstruction. The resulting image has no trace of the glasses frame or of the reflection and shade caused by the glasses. The experimental results show that the proposed method provides an effective solution to the problem of glasses occlusion and we believe that this method can also be used to enhance the performance of face recognition systems.

Original language	English
Pages (from-to)	805-811
Number of pages	7
Journal	IEEE Transactions on Pattern Analysis and Machine Intelligence
Volume	27
Issue number	5
DOIs	https://doi.org/10.1109/TPAMI.2005.103
Publication status	Published - 2005 May

Keywords

Face recognition
Face reconstruction
Face synthesis
Glasses removal
Recursive error compensation

ASJC Scopus subject areas

Software
Computer Vision and Pattern Recognition
Computational Theory and Mathematics
Artificial Intelligence
Applied Mathematics

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10.1109/TPAMI.2005.103

Cite this

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title = "Glasses removal from facial image using recursive error compensation",

abstract = "In this paper, we propose a new method of removing glasses from a human frontal facial image. We first detect the regions occluded by the glasses and generate a natural looking facial image without glasses by recursive error compensation using PCA reconstruction. The resulting image has no trace of the glasses frame or of the reflection and shade caused by the glasses. The experimental results show that the proposed method provides an effective solution to the problem of glasses occlusion and we believe that this method can also be used to enhance the performance of face recognition systems.",

keywords = "Face recognition, Face reconstruction, Face synthesis, Glasses removal, Recursive error compensation",

author = "Park, {Jeong Seon} and Oh, {You Hwa} and Ahn, {Sang Chul} and Lee, {Seong Whan}",

note = "Funding Information: This research was supported by the Intelligent Robotics Development Program, one of the 21st Century Frontier R&D Programs funded by the Ministry of Science and Technology of Korea. A preliminary version of this paper has been presented at the International Conference on Audio-and Video-Based Biometric Person Authentication, Guildford, U.K., June 2003.",

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language = "English",

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T1 - Glasses removal from facial image using recursive error compensation

AU - Park, Jeong Seon

AU - Oh, You Hwa

AU - Ahn, Sang Chul

AU - Lee, Seong Whan

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PY - 2005/5

Y1 - 2005/5

N2 - In this paper, we propose a new method of removing glasses from a human frontal facial image. We first detect the regions occluded by the glasses and generate a natural looking facial image without glasses by recursive error compensation using PCA reconstruction. The resulting image has no trace of the glasses frame or of the reflection and shade caused by the glasses. The experimental results show that the proposed method provides an effective solution to the problem of glasses occlusion and we believe that this method can also be used to enhance the performance of face recognition systems.

AB - In this paper, we propose a new method of removing glasses from a human frontal facial image. We first detect the regions occluded by the glasses and generate a natural looking facial image without glasses by recursive error compensation using PCA reconstruction. The resulting image has no trace of the glasses frame or of the reflection and shade caused by the glasses. The experimental results show that the proposed method provides an effective solution to the problem of glasses occlusion and we believe that this method can also be used to enhance the performance of face recognition systems.

KW - Face recognition

KW - Face reconstruction

KW - Face synthesis

KW - Glasses removal

KW - Recursive error compensation

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JO - IEEE Transactions on Pattern Analysis and Machine Intelligence

JF - IEEE Transactions on Pattern Analysis and Machine Intelligence

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Glasses removal from facial image using recursive error compensation

Abstract

Keywords

ASJC Scopus subject areas

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