DocumentCode :
1877052
Title :
FacePerf: Benchmarks for Face Recognition Algorithms
Author :
Bolme, David S. ; Strout, Michelle ; Beveridge, J. Ross
Author_Institution :
Colorado State Univ., Fort Collins
fYear :
2007
fDate :
27-29 Sept. 2007
Firstpage :
114
Lastpage :
119
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%.
Keywords :
Haar transforms; biometrics (access control); computational complexity; computer vision; face recognition; graph theory; image classification; image matching; principal component analysis; C biometric performance benchmark algorithms; C++ biometric performance benchmark algorithms; FacePerf benchmarks; Haar-based face detection; OpenCV cascade classifier; computer vision; cosine approximation; elastic bunch graph matching; face recognition algorithms; principal components analysis; Benchmark testing; Biometrics; Clocks; Computer science; Computer vision; Face detection; Face recognition; Image databases; Principal component analysis; Space technology;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Workload Characterization, 2007. IISWC 2007. IEEE 10th International Symposium on
Conference_Location :
Boston, MA
Print_ISBN :
978-1-4244-1561-8
Electronic_ISBN :
978-1-4244-1562-5
Type :
conf
DOI :
10.1109/IISWC.2007.4362187
Filename :
4362187
Link To Document :
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