Thank you for being alive: how we chose passive liveness

Hello everyone! My name is Natalya Bessonova, I am the project director of the digital identity block of Rostelecom. In this article I want to talk about how we chose passive liveness from one face image for the Unified Biometric System.





There are not many articles on Habrรฉ devoted to liveness in biometric systems, and those that exist describe methods and algorithms for determining liveness, or, more simply, the belonging of biometric samples to a living person. Let's pay tribute to their authors - the articles are interesting and informative, but what if we are interested in how well they work on data that is not included in any of the open data sets? How do you know if the liveness is really good or bad and which one should you choose if necessary? In this article, I will describe an approach to choosing a passive singleshot-liveness (i.e., one image at a time) of a face for the Unified Biometric System .





Why do you need liveness

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266.501





160.091





0.395





542.772





471.081





0.320





vendor1_v2





0.042





155.626





108.508





0.395





381.548





367.438





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vendor2_v2_CPU





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874.527





21.748





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910.202





60.381





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vendor2_v2_GPU





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863.651





26.629





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903.743





62.957





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vendor1_v3





0.094





110.198





100.997





0.811





293.092





242.255





0.437





vendor3





0.153





146.217





82.217





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360.056





324.149





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vendor2_v1





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874.294





35.319





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1060.088





121.127





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vendor4





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444.085





35.818





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512.427





106.987





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vendor5_v3





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160.426





298.351





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683.258





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vendor6





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111.626





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373.670





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