FaceID: A face detection and recognition system

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Description

A face detection system that automatically locates faces in gray-level images is described. Also described is a system which matches a given face image with faces in a database. Face detection in an Image is performed by template matching using templates derived from a selected set of normalized faces. Instead of using original gray level images, vertical gradient images were calculated and used to make the system more robust against variations in lighting conditions and skin color. Faces of different sizes are detected by processing the image at several scales. Further, a coarse-to-fine strategy is used to speed up the ... continued below

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12 p.

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Shah, M.B.; Rao, N.S.V.; Olman, V.; Uberbacher, E.C. & Mann, R.C. December 31, 1996.

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This article is part of the collection entitled: Office of Scientific & Technical Information Technical Reports and was provided by UNT Libraries Government Documents Department to Digital Library, a digital repository hosted by the UNT Libraries. It has been viewed 31 times , with 4 in the last month . More information about this article can be viewed below.

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Description

A face detection system that automatically locates faces in gray-level images is described. Also described is a system which matches a given face image with faces in a database. Face detection in an Image is performed by template matching using templates derived from a selected set of normalized faces. Instead of using original gray level images, vertical gradient images were calculated and used to make the system more robust against variations in lighting conditions and skin color. Faces of different sizes are detected by processing the image at several scales. Further, a coarse-to-fine strategy is used to speed up the processing, and a combination of whole face and face component templates are used to ensure low false detection rates. The input to the face recognition system is a normalized vertical gradient image of a face, which is compared against a database using a set of pretrained feedforward neural networks with a winner-take-all fuser. The training is performed by using an adaptation of the backpropagation algorithm. This system has been developed and tested using images from the FERET database and a set of images obtained from Rowley, et al and Sung and Poggio.

Physical Description

12 p.

Notes

OSTI as DE97001735

Source

  • Photonics East `96: International Society for Optical Engineering (SPIE) conference and exhibition on photonic sensors and controls for commercial applications, Boston, MA (United States), 19-21 Nov 1996

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  • Other: DE97001735
  • Report No.: CONF-961113--10
  • Grant Number: AC05-96OR22464
  • Office of Scientific & Technical Information Report Number: 427004
  • Archival Resource Key: ark:/67531/metadc677541

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  • December 31, 1996

Added to The UNT Digital Library

  • July 25, 2015, 2:20 a.m.

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  • Jan. 19, 2016, 1:37 p.m.

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Shah, M.B.; Rao, N.S.V.; Olman, V.; Uberbacher, E.C. & Mann, R.C. FaceID: A face detection and recognition system, article, December 31, 1996; Tennessee. (digital.library.unt.edu/ark:/67531/metadc677541/: accessed September 24, 2017), University of North Texas Libraries, Digital Library, digital.library.unt.edu; crediting UNT Libraries Government Documents Department.