IEEE Trans Pattern Anal Mach Intell. 2018 Feb;40(2):332-351. doi: 10.1109/TPAMI.2017.2669035. Epub 2017 Feb 14.
Biometrics is the technique of automatically recognizing individuals based on their biological or behavioral characteristics. Various biometric traits have been introduced and widely investigated, including fingerprint, iris, face, voice, palmprint, gait and so forth. Apart from identity, biometric data may convey various other personal information, covering affect, age, gender, race, accent, handedness, height, weight, etc. Among these, analysis of demographics (age, gender, and race) has received tremendous attention owing to its wide real-world applications, with significant efforts devoted and great progress achieved. This survey first presents biometric demographic analysis from the standpoint of human perception, then provides a comprehensive overview of state-of-the-art advances in automated estimation from both academia and industry. Despite these advances, a number of challenging issues continue to inhibit its full potential. We second discuss these open problems, and finally provide an outlook into the future of this very active field of research by sharing some promising opportunities.
生物识别技术是一种基于个体的生物或行为特征自动识别个体的技术。已经引入并广泛研究了各种生物识别特征，包括指纹、虹膜、面部、语音、掌纹、步态等。除了身份，生物识别数据还可能传达各种其他个人信息，包括情感、年龄、性别、种族、口音、惯用手、身高、体重等。在这些信息中，由于其广泛的实际应用，人口统计学（年龄、性别和种族）的分析受到了极大的关注，学术界和工业界都投入了大量的精力并取得了很大的进展。本调查首先从人类感知的角度介绍生物识别人口统计学分析，然后全面概述学术界和工业界在自动估计方面的最新进展。尽管取得了这些进展，但仍有一些具有挑战性的问题继续限制其潜力的充分发挥。我们接着讨论了这些开放的问题，最后通过分享一些有前途的机会，展望了这个非常活跃的研究领域的未来。
