SQUEEZE: a hybrid cloud-edge implementation
Type: Bachelor EE/CS/HMI
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Many airports have implemented an automatic border control system. A traveler presents its biometric passport containing facial biometric information stored in a template, the system takes a facial image, compares it to the template and if they match sufficiently according to an algorithm, the system allows access.
This is one of many verification examples in which a biometric template is compared to a sensor measurement of a fingerprint, face or iris. The template storage, sensor and matching algorithm are three independent components. The EU GDP Regulation implies strict requirements on the secure storage and safe use of biometric templates. One solution is to integrate the template storage, sensor and algorithm in a single tamperproof personal device. This device communicates the verification result to a central system without exposing biometric information. An example of such device is a debit/credit bank (smart) cards with an integrated fingerprint sensor, see for example https://www.fingerprints.com/solutions/payments/. Another example would be a trusted device that can be used for face verification.
An interesting idea to explore is the impact of sparse models on face recognition performance; another idea is to split the verification over a device (either card or MCU, can be simulated) and the cloud and study the impact of performance.
This topic can be taken by two students; in a first session we’ll decide who is doing what.