Multi-Frame Super-Resolution for Face Recognition

Author

Wheeler, Frederick W. ; Liu, Xiaoming ; Tu, Peter H.

fYear

2007

fDate

27-29 Sept. 2007

Firstpage

1

Lastpage

6

Abstract

Face recognition at a distance is a challenging and important law-enforcement surveillance problem, with low image resolution and blur contributing to the difficulties. We present a method for combining a sequence of video frames of a subject in order to create a super-resolved image of the face with increased resolution and reduced blur. An Active Appearance Model (AAM) of face shape and appearance is fit to the face in each video frame. The AAM fit provides the registration used by a robust image super-resolution algorithm that iteratively solves for a higher resolution face image from a set of video frames. This process is tested with real-world outdoor video using a PTZ camera and a commercial face recognition engine. Both improved visual perception and automatic face recognition performance are observed in these experiments.

Keywords

face recognition; image registration; image resolution; image sequences; iterative methods; video surveillance; PTZ camera; active appearance model; face recognition; image registration; iterative method; law-enforcement surveillance problem; multiframe image resolution; video frame sequence; visual perception; Active appearance model; Active shape model; Cameras; Engines; Face recognition; Image resolution; Iterative algorithms; Robustness; Surveillance; Testing;

fLanguage

English

Publisher

ieee

Conference_Titel

Biometrics: Theory, Applications, and Systems, 2007. BTAS 2007. First IEEE International Conference on

Conference_Location

Crystal City, VA

Print_ISBN

978-1-4244-1596-0

Electronic_ISBN

978-1-4244-1597-7

Type

conf

DOI

10.1109/BTAS.2007.4401949

Filename

4401949