Title Krause, A. F., Essig, K., Wild-Wall, N., Ressel, C. (2024), A proposal for the concept of Pro-adaptive Cognitive Assistive Technology. Abstract, accepted at Human Factors and Ergonomics Societey Europe (HFES).
Abstract Assistive Technology is becoming an integral part of our daily live, supporting people in different areas, for example while driving a car or cognitive demanding tasks at work or home. Yet, existing Assistive Technology often only considers the current situational context and capabilities of a user.
Title Krause, A. F., Ferger, A., Pitsch, K. (2023). Anonymization of Persons in Videos of Authentic Social Interaction: Model Selection and Parameter Optimization. In: 10th International Conference on CMC and Social Media Corpora for the Humanities (CMC-Corpora 2023), Mannheim.
Abstract Automatic anonymization of persons in video recordings requires robust detection of face and head areas. Machine learning-based face and posture detectors provide bounding boxes of face and head regions, but specific parameters need to be optimized to maximize the number of correctly anonymized persons and minimize manual annotation and verification efforts.
Krause, A.F., Ferger, A., Pitsch, K. (2023). Detecting and Tracking Persons in Video Recordings of Authentic Social Interaction: Analysis and Anonymization. Computational and Quantitative Approaches to Multimodal Video Analysis (CAMVA 2023). accepted.
https://doi.org/10.1007/978-3-031-10467-1_47
Abstract Compromised near-body electronic devices, like an eye tracker or a brain-computer interface, can leak private, highly sensitive biometric or medical data. Such data must be protected at all costs to avoid mass-surveillance and hacking attempts. We review the current, dire state of network security caused by complex protocols, closed-source software and proprietary hardware. To tackle the issue, we discuss a concept that protects privacy by combining three elements: data diodes, strong encryption and true random number generators.
