FacePerf: Benchmarks for face recognition algorithms

David S. Bolme, Michelle Strout, J. Ross Beveridge

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Scopus citations

Abstract

In this paper we present a collection of C and C++ biometric performance benchmark algorithms called FacePerf. The benchmark includes three different face recognition algorithms that are historically important to the face recognition community: Haar-based face detection, Principal Components Analysis, and Elastic Bunch Graph Matching. The algorithms are fast enough to be useful in realtime systems; however, improving performance would allow the algorithms to process more images or search larger face databases. Bottlenecks for each phase in the algorithms have been identified. A cosine approximation was able to reduce the execution time of the Elastic Bunch Graph Matching implementation by 32%.

Original languageEnglish (US)
Title of host publicationProceedings of the 2007 IEEE International Symposium on Workload Characterization, IISWC
Pages114-119
Number of pages6
DOIs
StatePublished - 2007
Externally publishedYes
Event2007 IEEE International Symposium on Workload Characterization, IISWC - Boston, MA, United States
Duration: Sep 27 2007Sep 29 2007

Publication series

NameProceedings of the 2007 IEEE International Symposium on Workload Characterization, IISWC

Conference

Conference2007 IEEE International Symposium on Workload Characterization, IISWC
Country/TerritoryUnited States
CityBoston, MA
Period9/27/079/29/07

ASJC Scopus subject areas

  • Computer Science Applications
  • Hardware and Architecture
  • Electrical and Electronic Engineering

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