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Improving long range and high magnification face recognition: Database acquisition, evaluation, and enhancement
 

Summary: Improving long range and high magnification face recognition:
Database acquisition, evaluation, and enhancement
Yi Yao a
, Besma R. Abidi a,*, Nathan D. Kalka b
, Natalia A. Schmid b
, Mongi A. Abidi a
a
Imaging, Robotics, and Intelligent Systems Laboratory, The University of Tennessee, Knoxville, TN 37996, USA
b
West Virginia University, Morgantown, WV 26506, USA
Received 23 April 2007; accepted 4 September 2007
Available online 29 September 2007
Abstract
In this paper, we describe a face video database, UTK-LRHM, acquired from long distances and with high magnifications. Both
indoor and outdoor sequences are collected under uncontrolled surveillance conditions. To our knowledge, it is the first database to pro-
vide face images from long distances (indoor: 1016 m and outdoor: 50300 m). The corresponding system magnifications range from
3 to 20 for indoor and up to 284 for outdoor. This database has applications in experimentations with human identification and
authentication in long range surveillance and wide area monitoring. Deteriorations unique to long range and high magnification face
images are investigated in terms of face recognition rates based on the UTK-LRHM database. Magnification blur is shown to be a major
degradation source, the effect of which is quantified using a novel blur assessment measure and alleviated via adaptive deblurring algo-

  

Source: Abidi, Mongi A. - Department of Electrical and Computer Engineering, University of Tennessee

 

Collections: Computer Technologies and Information Sciences