IARPA Janus Benchmark - C: Face Dataset and Protocol

Brianna Maze, Jocelyn C. Adams, James A. Duncan, N. Kalka, Tim Miller, C. Otto, Anil K. Jain, W. T. Niggel, Janet Anderson, J. Cheney, P. Grother
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引用次数: 452

Abstract

Although considerable work has been done in recent years to drive the state of the art in facial recognition towards operation on fully unconstrained imagery, research has always been restricted by a lack of datasets in the public domain. In addition, traditional biometrics experiments such as single image verification and closed set recognition do not adequately evaluate the ways in which unconstrained face recognition systems are used in practice. The IARPA Janus Benchmark–C (IJB-C) face dataset advances the goal of robust unconstrained face recognition, improving upon the previous public domain IJB-B dataset, by increasing dataset size and variability, and by introducing end-to-end protocols that more closely model operational face recognition use cases. IJB-C adds 1,661 new subjects to the 1,870 subjects released in IJB-B, with increased emphasis on occlusion and diversity of subject occupation and geographic origin with the goal of improving representation of the global population. Annotations on IJB-C imagery have been expanded to allow for further covariate analysis, including a spatial occlusion grid to standardize analysis of occlusion. Due to these enhancements, the IJB-C dataset is significantly more challenging than other datasets in the public domain and will advance the state of the art in unconstrained face recognition.
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IARPA Janus Benchmark - C:人脸数据集和协议
尽管近年来已经做了大量的工作来推动面部识别技术的发展,使其朝着完全不受约束的图像操作的方向发展,但研究一直受到公共领域缺乏数据集的限制。此外,传统的生物识别实验,如单图像验证和闭集识别,并不能充分评估无约束人脸识别系统在实践中的使用方式。IARPA Janus Benchmark-C (IJB-C)人脸数据集推进了鲁棒无约束人脸识别的目标,通过增加数据集的大小和可变性,并通过引入端到端协议,更紧密地模拟操作人脸识别用例,改进了以前的公共领域IJB-B数据集。IJB-C在IJB-B发布的1,870个科目的基础上增加了1,661个新科目,更加强调科目职业和地理来源的遮挡和多样性,目标是提高全球人口的代表性。IJB-C图像上的注释已经扩展,以允许进一步的协变量分析,包括空间遮挡网格,以标准化遮挡分析。由于这些增强,IJB-C数据集比公共领域的其他数据集更具挑战性,并将推动无约束人脸识别的最新发展。
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