Finding and Improving the Key-Frames of Long Video Sequences for Face Recognition

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

12 Citations (Scopus)

Abstract

Face recognition systems are very sensitive to the quality and resolution of their input face images. This makes such systems unreliable when working with long surveillance video sequences without employing some selection and enhancement algorithms. On the other hand, processing all the frames of such video sequences by any enhancement or even face recognition algorithm is demanding. Thus, there is a need for a mechanism to summarize the input video sequence to a set of key-frames and then applying an enhancement algorithm to this subset. This paper presents a system doing exactly this. The system uses face quality assessment to select the key-frames and a hybrid super-resolution to enhance the face image quality. The suggested system that employs a linear associator face recognizer to evaluate the enhanced results has been tested on real surveillance video sequences and the experimental results show promising results.
Original languageEnglish
Title of host publicationIEEE 4th International Conference on Biometrics Theory, Applications and Systems (BTAS), Washington DC, USA
Number of pages6
Place of PublicationWashington, DC, USA
PublisherIEEE Press
Publication date27 Sept 2010
ISBN (Print)978-1-4244-7581-0
ISBN (Electronic)978-1-4244-7580-3
DOIs
Publication statusPublished - 27 Sept 2010
Event IEEE 4th International Conference on Biometrics Theory, Applications and Systems (BTAS) - Washington DC, United States
Duration: 27 Sept 201029 Sept 2010

Conference

Conference IEEE 4th International Conference on Biometrics Theory, Applications and Systems (BTAS)
Country/TerritoryUnited States
CityWashington DC
Period27/09/201029/09/2010

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