NDLI: Quality assessment and restoration of face images in long range/high zoom video.

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Quality assessment and restoration of face images in long range/high zoom video.

Content Provider	CiteSeerX
Author	Abidi, Mongi Yao, Yi Abidi, Besma
Abstract	Most existing face related research is restricted to close range applications with low and constant system magnifications (camera zoom). To improve the performance of face recognition algorithms in wide area surveillance applications, we initiate a study regarding the effects of increased system magnifications and observation distances on face recognition rates (FRR). We first describe a new face video database including still face images and video sequences from long distances (indoor: 10m-20m and outdoor: 50m-300m). The corresponding system magnification is elevated from less than 3 × to 20 × for indoor and up to 375 × for outdoor. Deteriorations unique to high magnification and long range face images are investigated. Magnification blur proves to be a major degradation source for face recognition and is addressed via blur assessment and deblurring algorithms. Experimental results validate a relative improvement of up to 26 % in FRR after assessment and restoration of high magnification face images. 2
File Format	PDF
Access Restriction	Open
Subject Keyword	Blur Assessment High Magnification Range Application Video Sequence Camera Zoom High Magnification Face Image Long Distance Corresponding System Magnification Observation Distance Face Recognition Algorithm Wide Area Surveillance Application Relative Improvement Long Range High Zoom Video Constant System Magnification Face Image New Face Video Database Quality Assessment Magnification Blur Face Recognition Increased System Magnification Major Degradation Source Face Recognition Rate Experimental Result Long Range Face Image
Content Type	Text

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