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dc.contributor.authorXu, Xiang
dc.contributor.authorLiu, Wan-Quan
dc.contributor.authorLi, Ling
dc.identifier.citationXu, X. and Liu, W. and Li, L. 2014. Low Resolution Face Recognition in Surveillance Systems. Journal of Computer and Communications. 2: pp. 70-77.

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.

dc.publisherScientific Research Publishing, Inc.
dc.subjectSurveillance Camera
dc.subjectFace Recognition
dc.subjectVery Low Resolution
dc.titleLow Resolution Face Recognition in Surveillance Systems
dc.typeJournal Article
dcterms.source.titleJournal of Computer and Communications

This open access article is distributed under the Creative Commons license

curtin.departmentDepartment of Computing
curtin.accessStatusOpen access

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