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|Author(s):||P J. Phillips; J. R. Beveridge; David Bolme; Bruce A. Draper; Geof H. Givens; Yui M. Lui; Hao Zhang; W T. Scruggs; Kevin W. Bowyer; Patrick J. Flynn; Su L. Cheng;|
|Title:||The Challenge of Face Recognition From Digital Point-and-Shoot Cameras|
|Published:||June 25, 2013|
|Abstract:||Face recognition is appearing in personal and commercial products at an astonishing rate, yet reliable face recognition remains challenging. Users expect a lot; they want to snap pictures and have their friends, family and acquaintances recognized. This scenario is playing out millions of times a day, and despite its simplicity face recognition in this context is hard. Roughly speaking, failure rates in the 4 to 8 out of 10 range are common. In contrast, using well controlled imagery error rates drop as low as 1 in 1,000. To spur advancement on point-and-shoot face recognition this paper presents a new challenge problem consisting of 9,376 images of 293 people balanced with respect to distance to the camera, alternative sensors, frontal versus not-frontal views, and varying location. Results are presented for two public baseline algorithms and a high-quality commercial algorithm. At false accept rates of 0.001 and 0.01 the best verification rates presented are 0.21 and 0.41 respectively. Pilot studies illustrate covariates analysis, non-match score sensitivity to covariates and an image quality analysis suggesting commonly suggested quality measures don‰t capture what is making the problem challenging.|
|Proceedings:||IEEE Conference on Computer Vision and Pattern Recognition|
|Dates:||June 25-27, 2013|
|Research Areas:||Biometrics, Information Technology|
|PDF version:||Click here to retrieve PDF version of paper (4MB)|