Biometric Scores 2014 (BIOSCOTE 2014)

Description

This dataset contains raw scores in plain text format of several biometric (face and speaker) recognition systems applied on several datasets such as BANCA, Arface, FRGC, GBU, LFW, Multi-PIE, MOBIO, CAS-PEAL, NIST SRE 2012.

The biometric recognition systems are described in the aforementioned manuscript and encompasses Gaussian mixture models, inter-session variability modelling, joint factor analysis and probabilistic linear discriminant analysis.

The databases considered are the following ones:

BANCA

AR face database

Face Recognition Grand Challenge version 2

The Good, The Bad and the Ugly

Labeled Faces in the Wild

Multi-PIE

MOBIO

CAS-PEAL

NIST Speaker Recognition Evaluation 2012

These scores allow to replicate easily and quickly the plots of the manuscript by using the following package:
http://pypi.python.org/pypi/xbob.thesis.elshafey2014

Citation

If you use this dataset in your publication, we would appreciate that you cite the following thesis:

Laurent El Shafey, “Scalable Probabilistic Models for Face and Speaker Recognition”, PhD thesis, 2014.
http://publications.idiap.ch/index.php/publications/show/2830

数据集描述

本数据集以纯文本格式存储了多款生物特征（人脸与说话人）识别系统的原始评分，这些系统被应用于BANCA、AR人脸数据库（AR face database）、人脸识别挑战赛第二版（Face Recognition Grand Challenge version 2，FRGC）、好坏丑数据集（The Good, The Bad and the Ugly，GBU）、野生标注人脸集（Labeled Faces in the Wild，LFW）、Multi-PIE、MOBIO、CAS-PEAL以及NIST 2012说话人识别评测集（NIST Speaker Recognition Evaluation 2012）等多个公开数据集。

上述生物特征识别系统已在本数据集配套的研究手稿中详述，其涵盖高斯混合模型（Gaussian mixture models）、会话间变异性建模、联合因子分析以及概率线性判别分析（probabilistic linear discriminant analysis）。

本次实验涉及的数据库如下：
- BANCA
- AR人脸数据库
- 人脸识别挑战赛第二版（FRGC）
- 好坏丑数据集（GBU）
- 野生标注人脸集（LFW）
- Multi-PIE
- MOBIO
- CAS-PEAL
- NIST 2012说话人识别评测集

通过以下工具包，用户可便捷快速地复现手稿中的各类图表：http://pypi.python.org/pypi/xbob.thesis.elshafey2014

引用说明

若您在学术出版物中使用本数据集，烦请引用以下博士学位论文：
洛朗·埃尔·沙菲（Laurent El Shafey），《面向人脸与说话人识别的可扩展概率模型》（Scalable Probabilistic Models for Face and Speaker Recognition），2014年博士学位论文。
可通过以下链接获取原文：http://publications.idiap.ch/index.php/publications/show/2830