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Title: Face Recognition from Oak Ridge (FaRO)

Abstract

Many universities have published highly accurate open source face recognition algorithms, but configuring and using those algorithms can be very difficult due to poor documentation and challenges with installing the right software and libraries. Comparing research results is also a problem due to uncontrolled research methods. Provide baseline face recognition implementations that can be used for evaluating algorithm accuracy. The software provides a consistent web service interface to face recognition algorithms that can be used to support research in biometrics. The software uses protobuf and grpc services to publish standardized interfaces to the algorithms. The software also provides Docker container support which allows services to be easily started and configured on new machines. Reproducible baseline configurations are provided to serve as bench marks for publications in this area.

Authors:
 [1];  [1]
  1. Oak Ridge National Laboratory
Publication Date:
Research Org.:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1512255
Report Number(s):
Face Recognition from Oak Ridge (FaRO); 005847MLTPL00
DOE Contract Number:  
AC05-00OR22725
Resource Type:
Software
Software Revision:
00
Software Package Number:
005847
Software CPU:
MLTPL
Open Source:
Yes
Source Code Available:
Yes
Country of Publication:
United States

Citation Formats

Bolme, David S, and Cornett lii, David C. Face Recognition from Oak Ridge (FaRO). Computer software. https://www.osti.gov//servlets/purl/1512255. Vers. 00. USDOE. 15 Feb. 2019. Web.
Bolme, David S, & Cornett lii, David C. (2019, February 15). Face Recognition from Oak Ridge (FaRO) (Version 00) [Computer software]. https://www.osti.gov//servlets/purl/1512255.
Bolme, David S, and Cornett lii, David C. Face Recognition from Oak Ridge (FaRO). Computer software. Version 00. February 15, 2019. https://www.osti.gov//servlets/purl/1512255.
@misc{osti_1512255,
title = {Face Recognition from Oak Ridge (FaRO), Version 00},
author = {Bolme, David S and Cornett lii, David C},
abstractNote = {Many universities have published highly accurate open source face recognition algorithms, but configuring and using those algorithms can be very difficult due to poor documentation and challenges with installing the right software and libraries. Comparing research results is also a problem due to uncontrolled research methods. Provide baseline face recognition implementations that can be used for evaluating algorithm accuracy. The software provides a consistent web service interface to face recognition algorithms that can be used to support research in biometrics. The software uses protobuf and grpc services to publish standardized interfaces to the algorithms. The software also provides Docker container support which allows services to be easily started and configured on new machines. Reproducible baseline configurations are provided to serve as bench marks for publications in this area.},
url = {https://www.osti.gov//servlets/purl/1512255},
doi = {},
year = {2019},
month = {2},
note =
}