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Fraunhofer-Institut für Graphische Datenverarbeitung
For our Competence Center Smart Living and Biometric Technologies we’re looking for a

Master Thesis Proposal: Cross-device biometric verification and the benefit of multi-algorithmic biometric fusion

Kennziffer: IGD-2017-44
Biometrics is a rapidly growing technology that aims to identify or verify people identities based on their physical or behavioral properties. Multi-biometrics are implemented to use a number f biometric information sources to create a unified decision. This aims at enhancing performance and avoiding the shortcomings of conventional single source biometrics such as sensitivity to noisy data or capture environment while maintaining high accuracy. One of these shortcomings are the negative effect of cross-device biometric verification, e.g. using different smart phones and capture devices for the enrolment and verification of face images.
Was Sie mitbringen
  • Interest in computer vision and machine learning
  • Programming skills
Study programs: Informatics, electrical engineering, mathematics, physics.
Was Sie erwarten können
A thorough state of the art study should be carried to help build up to the proposed solution. The work includes designing the experiment to use two different biometric modalities with cross-device databases. A number of standard and state of the art verification approaches should be implemented as baseline solutions. These algorithms will be used as multiple sources to feed into a fusion approach that will result in a unified biometric verification decision. Different fusion approaches should be investigated and analyzed to assist their benefits in such a scenario. Based on initial analyses, a fusion solution should be proposed to achieve the best accuracy when facing cross-device biometric deployment. Final experiments and results should be analyzed thoroughly.
Key literature:
[1] B. Amos, B. Ludwiczuk, M. Satyanarayanan, "Openface: A general-purpose face recognition library with mobile applications," CMU-CS-16-118, CMU School of Computer Science, Tech. Rep., 2016.
[2] Naser Damer, Kristiyan Dimitrov: Practical View on Face Presentation Attack Detection. BMVC 2016.
[3] Ivana Chingovska, J. Yang, Zhen Lei, Dong Yi, Stan Z. Li, Olga Kähm, Christian Glaser, Naser Damer, Arjan Kuijper, Alexander Nouak, Jukka Komulainen, Tiago Freitas Pereira, Shubham Gupta, Shubham Khandelwal, Shubham Bansal, Ayush Rai, Tarun Krishna, Dushyant Goyal, Muhammad-Adeel Waris, Honglei Zhang, Iftikhar Ahmad, Serkan Kiranyaz, Moncef Gabbouj, Roberto Tronci, Maurizio Pili, Nicola Sirena, Fabio Roli, Javier Galbally, Julian Fiérrez, Allan da Silva Pinto, Hélio Pedrini, W. S. Schwartz, Anderson Rocha, André Anjos, Sébastien Marcel: The 2nd competition on counter measures to 2D face spoofing attacks. ICB 2013: 1-6

In case of identical qualifications, preference will be given to severely disabled candidates.
The Fraunhofer-Gesellschaft is committed to providing equal career opportunities for men and women.

Fraunhofer is Europe’s largest application-oriented research organization. Our research efforts are geared entirely to people’s needs: health, security, communication, energy and the environment. As a result, the work undertaken by our researchers and developers has a significant impact on people’s lives. We are creative. We shape technology. We design products. We improve methods and techniques. We open up new vistas.

Ansprechpartner: Naser Damer
Fraunhoferstr. 5
64283 Darmstadt
E-Mail: naser.damer@igd.fraunhofer.de
Fraunhofer-Institut für Graphische Datenverarbeitung


Erschienen auf academics.de am 31.08.2017
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