Bachelor/Masterthesis - "Computer Vision for Biometrics"

Biometrics is a rapidly growing technology that aims to identify or verify people's identities based on their physical or behavioural properties. Different aspects of biometric technology are active research fields. Enhancing the accuracy of biometric comparisons, securing the biometric templates, managing fast searches in biometric databases, and detecting different attacks on biometric systems, are all essential advancements to enable a wider and more secure deployment of the technology. Most biometric systems are based on image analyses. Therefore, exciting challenges in the computer vision domain are inherited by biometric systems. Such challenges are related to miniature deep learning networks, explainable decisions, and domain adaption.

Our team is offering several open thesis positions to tackle these challenges. Interested students from Computer Science, Data Science, Physics, Statistics, and Mathematics, are encouraged to apply. The exact details of the thesis topic can be built on the available topics and the competencies and interests of the student.

What you will do

The goal of the thesis is to perform state-of-the-art research in computer vision and machine learning for biometrics applications. The exact topic description can be tailored based on the research direction and student interests. The topics can target one of the following domains:

• Robust Face Recognition: Explore novel methods to enhance face recognition performance in challenging conditions, such as varying lighting, pose, and occlusion. Develop strategies to train robust biometric systems in the presence of noisy or incomplete data, improving real-world performance.
• Knowledge Distillation: Investigate techniques to compress complex biometric models while preserving accuracy, enabling efficient deployment on resource-constrained devices.
• Uncertainty Quantification: Focus on methods to estimate and represent the uncertainty associated with biometric predictions, leading to more reliable systems.
• Explainability: Work on developing explainable AI techniques for biometric systems, enhancing transparency and trust in these critical technologies.
• Fairness: Address the critical issue of fairness in biometric systems by developing methods to mitigate bias and ensure equitable performance across different demographic groups.

What you bring to the table

Required skills: Interest in machine learning and computer vision, good programming skills.

Study programs: Computer Science, Data Science, Physics, Statistics, and Mathematics

The weekly working time is 39 hours. We value and promote the diversity of our employees' skills and therefore welcome all applications - regardless of age, gender, nationality, ethnic and social origin, religion, ideology, disability, sexual orientation and identity. Severely disabled persons are given preference in the event of equal suitability. 

With its focus on developing key technologies that are vital for the future and enabling the commercial utilization of this work by business and industry, Fraunhofer plays a central role in the innovation process. As a pioneer and catalyst for groundbreaking developments and scientific excellence, Fraunhofer helps shape society now and in the future. 

Interested? Apply online now. We look forward to getting to know you!

Fraunhofer Institute for Computer Graphics Research IGD 

www.igd.fraunhofer.de 

Requisition Number: 78283                Application Deadline: 05/19/2025