Assessing the accuracy of four popular face recognition tools for inferring gender, age, and race

• Main Authors: JUNG, Soon-Gyu, AN, Jisun, KWAK, Haewoon, SALMINEN, Joni, JANSEN, Bernard J.
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2018
• Subjects: Computational social science; Measurement study; Computational Engineering; Databases and Information Systems
• Online Access: https://ink.library.smu.edu.sg/sis_research/5338; https://ink.library.smu.edu.sg/context/sis_research/article/6342/viewcontent/17839_77973_1_PB.pdf
• Institution: Singapore Management University

In this research, we evaluate four widely used face detection tools, which are Face++, IBM Bluemix Visual Recognition, AWS Rekognition, and Microsoft Azure Face API, using multiple datasets to determine their accuracy in inferring user attributes, including gender, race, and age. Results show that t...