Low Resolution Face Recognition in Surveillance Systems

In surveillance systems, the captured facial images are often very small and different from the low-resolution images down-sampled from high-resolution facial images. They generally lead to low performance in face recog-nition. In this paper, we study specific scenarios of face recognition with surv...

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Main Authors: Xu, Xiang, Liu, Wan-Quan, Li, Ling
Format: Journal Article
Published: Scientific Research Publishing, Inc. 2014
Subjects:
Online Access:http://hdl.handle.net/20.500.11937/4636
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author Xu, Xiang
Liu, Wan-Quan
Li, Ling
author_facet Xu, Xiang
Liu, Wan-Quan
Li, Ling
author_sort Xu, Xiang
building Curtin Institutional Repository
collection Online Access
description In surveillance systems, the captured facial images are often very small and different from the low-resolution images down-sampled from high-resolution facial images. They generally lead to low performance in face recog-nition. In this paper, we study specific scenarios of face recognition with surveillance cameras. Three important factors that influence face recognition performance are investigated: type of cameras, distance between the ob-ject and camera, and the resolution of the captured face images. Each factor is numerically investigated and analyzed in this paper. Based on these observations, a new approach is proposed for face recognition in real sur-veillance environment. For a raw video sequence captured by a surveillance camera, image pre-processing tech-niques are employed to remove the illumination variations for the enhancement of image quality. The face im-ages are further improved through a novel face image super-resolution method. The proposed approach is proven to significantly improve the performance of face recognition as demonstrated by experiments.
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institution Curtin University Malaysia
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last_indexed 2025-11-14T06:03:35Z
publishDate 2014
publisher Scientific Research Publishing, Inc.
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spelling curtin-20.500.11937-46362017-09-13T15:53:53Z Low Resolution Face Recognition in Surveillance Systems Xu, Xiang Liu, Wan-Quan Li, Ling Surveillance Camera Face Recognition Very Low Resolution In surveillance systems, the captured facial images are often very small and different from the low-resolution images down-sampled from high-resolution facial images. They generally lead to low performance in face recog-nition. In this paper, we study specific scenarios of face recognition with surveillance cameras. Three important factors that influence face recognition performance are investigated: type of cameras, distance between the ob-ject and camera, and the resolution of the captured face images. Each factor is numerically investigated and analyzed in this paper. Based on these observations, a new approach is proposed for face recognition in real sur-veillance environment. For a raw video sequence captured by a surveillance camera, image pre-processing tech-niques are employed to remove the illumination variations for the enhancement of image quality. The face im-ages are further improved through a novel face image super-resolution method. The proposed approach is proven to significantly improve the performance of face recognition as demonstrated by experiments. 2014 Journal Article http://hdl.handle.net/20.500.11937/4636 10.4236/jcc.2014.22013 Scientific Research Publishing, Inc. fulltext
spellingShingle Surveillance Camera
Face Recognition
Very Low Resolution
Xu, Xiang
Liu, Wan-Quan
Li, Ling
Low Resolution Face Recognition in Surveillance Systems
title Low Resolution Face Recognition in Surveillance Systems
title_full Low Resolution Face Recognition in Surveillance Systems
title_fullStr Low Resolution Face Recognition in Surveillance Systems
title_full_unstemmed Low Resolution Face Recognition in Surveillance Systems
title_short Low Resolution Face Recognition in Surveillance Systems
title_sort low resolution face recognition in surveillance systems
topic Surveillance Camera
Face Recognition
Very Low Resolution
url http://hdl.handle.net/20.500.11937/4636