A Score-Level Fusion Benchmark Database For Biometric Authentication. Poh, N. & Bengio, S. In Kanade, T., Jain, A., & Ratha, N. K., editors, 5th International Conference on Audio- and Video-Based Biometric Person Authentication, AVBPA, Lecture Notes in Computer Science, volume LNCS 3546, pages 474–483, 2005. Springer-Verlag. Paper abstract bibtex Fusing the scores of several biometric systems is a very promising approach to improve the overall system's accuracy. Despite many works in the literature, it is surprising that there is no coordinated effort in making a benchmark database available. It should be noted that fusion in this context consists not only of multimodal fusion, but also intramodal fusion, i.e., fusing systems using the same biometric modality but different features, or same features but using different classifiers. Building baseline systems from scratch often prevents researchers from putting more efforts in understanding the fusion problem. This paper describes a database of scores taken from experiments carried out on the XM2VTS face and speaker verification database. It then proposes several fusion protocols and provides some state-of-the-art tools to evaluate the fusion performance.
@inproceedings{poh:2005:avbpa:benchmark,
author = {N. Poh and S. Bengio},
title = {A Score-Level Fusion Benchmark Database For Biometric Authentication},
booktitle = {5th International Conference on Audio- and Video-Based Biometric Person Authentication, {AVBPA}, Lecture Notes in Computer Science},
editor = {T. Kanade and A. Jain and N. K. Ratha},
publisher = {Springer-Verlag},
volume = {LNCS 3546},
pages = {474--483},
year = 2005,
url = {publications/ps/poh_2005_avbpa_benchmark.ps.gz},
pdf = {publications/pdf/poh_2005_avbpa_benchmark.pdf},
djvu = {publications/djvu/poh_2005_avbpa_benchmark.djvu},
original = {2005/fusion_benchmark_avbpa},
topics = {biometric_authentication},
web = {http://dx.doi.org/10.1007/11527923_110},
abstract = {Fusing the scores of several biometric systems is a very promising approach to improve the overall system's accuracy. Despite many works in the literature, it is surprising that there is no coordinated effort in making a benchmark database available. It should be noted that fusion in this context consists not only of multimodal fusion, but also intramodal fusion, i.e., fusing systems using the same biometric modality but different features, or same features but using different classifiers. Building baseline systems from scratch often prevents researchers from putting more efforts in understanding the fusion problem. This paper describes a database of scores taken from experiments carried out on the XM2VTS face and speaker verification database. It then proposes several fusion protocols and provides some state-of-the-art tools to evaluate the fusion performance.},
categorie = {C},
}
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