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Visualization of faces from surveillance videos via face hallucination

Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSNConference contribution/Paperpeer-review

Published
  • Adam Makhfoudi
  • Somaya Al-Maadeed
  • Ahmed Bouridane
  • Graham Sexton
  • Richard Jiang
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Publication date11/2014
Host publication2014 International Conference on Control, Decision and Information Technologies (CoDIT)
PublisherIEEE
Pages701-705
Number of pages5
ISBN (electronic)9781479967735
<mark>Original language</mark>English
Event2014 International Conference on Control, Decision and Information Technologies - Metz, France
Duration: 3/11/20145/11/2014

Conference

Conference2014 International Conference on Control, Decision and Information Technologies
Abbreviated title(CoDIT
Country/TerritoryFrance
CityMetz
Period3/11/145/11/14

Conference

Conference2014 International Conference on Control, Decision and Information Technologies
Abbreviated title(CoDIT
Country/TerritoryFrance
CityMetz
Period3/11/145/11/14

Abstract

Face hallucination can be a useful tool for visualizing a low quality face into a visually better quality, making it an attractive technology for many applications. While faces in surveillance videos are usually at very low resolution, in this paper, we propose to use face hallucination technology to visualize faces from visual surveillance systems, and develop a weighted scheme to enhance the quality of face visualization from surveillance videos. Our experiment validated that in comparison with the classic eigenspace based face hallucination, our proposed weighted face hallucination strategy can help improve the overall quality of a facial image extracted from surveillance footage.