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http://dx.doi.org/10.5391/JKIIS.2013.23.5.423

Face Tracking and Recognition in Video with PCA-based Pose-Classification and (2D)2PCA recognition algorithm  

Kim, Jin-Yul (Dept. of Electronic Engineering, University of Suwo)
Kim, Yong-Seok (Dept. of Electronic Engineering, University of Suwo)
Publication Information
Journal of the Korean Institute of Intelligent Systems / v.23, no.5, 2013 , pp. 423-430 More about this Journal
Abstract
In typical face recognition systems, the frontal view of face is preferred to reduce the complexity of the recognition. Thus individuals may be required to stare into the camera, or the camera should be located so that the frontal images are acquired easily. However these constraints severely restrict the adoption of face recognition to wide applications. To alleviate this problem, in this paper, we address the problem of tracking and recognizing faces in video captured with no environmental control. The face tracker extracts a sequence of the angle/size normalized face images using IVT (Incremental Visual Tracking) algorithm that is known to be robust to changes in appearance. Since no constraints have been imposed between the face direction and the video camera, there will be various poses in face images. Thus the pose is identified using a PCA (Principal Component Analysis)-based pose classifier, and only the pose-matched face images are used to identify person against the pre-built face DB with 5-poses. For face recognition, PCA, (2D)PCA, and $(2D)^2PCA$ algorithms have been tested to compute the recognition rate and the execution time.
Keywords
Face Tracker; Face Pose Classification; Face Recognition; PCA; (2D)PCA; $(2D)^2PCA$;
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