Face Matching 1 to N

Fraudsters and money launderers have no place in today’s digital economy. To protect against fraud and financial crime, businesses online need to know and trust that their customers are who they claim to be – and that these customers continue to be trustworthy. Jumio uses the power of AI, biometrics, machine learning and certified liveness detection to help you rapidly convert more customers, stop fraudsters from infiltrating your online ecosystem and get in compliance with KYCIAML. The main goal of this project is to identify an individual from a face image by searching in a gallery of stored face images. The idea is to employ machine learning techniques to solve this problem. For this purpose, we want to review and evaluate existing solutions in order to develop an in-house approach. The fundamental challenges to tackle are: the particular conditions of our data, the huge amount of data to be handled and the quick response time demanded by our use case.

Faculty Supervisor:

Ioannis Mitliagkas

Student:

Partner:

Jumio

Discipline:

Computer science

Sector:

Professional, scientific and technical services

University:

Université de Montréal

Program: