Abstract
During the past few years face recognition technologies have greatly benefited from the huge progress in machine learning and now have achieved precision rates that are even comparable with humans. This allows us to apply face recognition technologies more effectively for a number of practical problems in various businesses like media monitoring, security, advertising, entertainment that we previously were not able to do due to low precision rates of existing face recognition technologies. In this paper we discuss how to build a face recognition system for media companies and share our experience gained from implementing one for Latvian national news agency LETA. Our contribution is: which technologies to use, how to build a practical training dataset, how large should it be, how to deal with unknown persons.
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Acknowledgement
The research leading to these results has received funding from the research project “Competence Centre of Information and Communication Technologies” of the EU Structural funds, contract No. 1.2.1.1/16/A/007 signed between IT Competence Centre and Central Finance and Contracting Agency, Research No. 2.5 “Automated visual material recognition and annotation system for LETA archive”.
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Sprogis, A., Freivalds, K., Cirule, E. (2018). Implementing a Face Recognition System for Media Companies. In: Lupeikiene, A., Vasilecas, O., Dzemyda, G. (eds) Databases and Information Systems. DB&IS 2018. Communications in Computer and Information Science, vol 838. Springer, Cham. https://doi.org/10.1007/978-3-319-97571-9_26
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