About the Project
visuAAL is a four-year (2020-2024) Marie Skłodowska-Curie Actions Innovative Training Network, funded by the European Union, that aims at bridging the knowledge gap between users’ requirements and the appropriate and secure use of video-based AAL technologies to deliver effective and supportive care to older adults managing their health and wellbeing.
visuAAL will seek to increase awareness and understanding of the context-specific ethical, legal, privacy and societal issues necessary to implement visual system across hospital, home and community settings, in a manner that protects and reassures users; outputs will stimulate the development of a new research perspective for constructively addressing privacy-aware video-based working solutions for assisted living.
visuAAL will provide a transdisciplinary and cross-sectoral combination of training, nonacademic placements, courses and workshops on scientific and complementary skills to 15 high achieving Early Stage Researchers (ESRs). These newly hired ESRs will contribute through their individual research projects to fulfil visuAAL's aims.
visuAAL brings together 5 universities:
• Chair of Communication Science, Human-Computer Interaction Center, RWTH Aachen University, Germany
• The Swedish Law and Informatics Research Institute (IRI), Stockholm University, Sweden
• The Trinity Centre for Practice and Healthcare Innovation, School of Nursing and Midwifery, Trinity College Dublin, Ireland
• Computer Vision Lab, TU Wien, Austria
• Department of Computing Technology, Universidad de Alicante, Spain (Project Coordinator)
This Consortium is complemented by 14 partner organizations from Austria, Germany, Ireland, Italy, Portugal, Spain, Sweden, and United Kingdom; that will contribute to the research and training activities.
For more information about visuAAL, see https://www.visuaal-itn.eu/
Project title:
Context recognition for the application of visual privacy
Objectives:
Most works conceal people’s visual privacy by using blurring or pixelatingeffects to modify an image. In a privacy-by-context approach, a level-based visualisation scheme to protect privacy is proposed. Each level establishes the way in which the video images are modified and displayed and, therefore, the provided protection degree. In this scheme, the appropriate level is dynamically selected according to the context, therefore modifying a non-protected image before it is displayed. The context has to provide enough information in order to empower people to adapt privacy to their preferences, in such a way that they can decide by whom, how and when they can be watched. The context is modelled by different variables: (i) the observer; (ii) the identity of the person (to retrieve the privacy profile); (iii) the closeness between the person and observer (e.g., relative, doctor or acquaintance); (iv) appearance (dressed?); (v) location (e.g., kitchen); and (vi) ongoing activity or detected event (e.g., cooking, watching TV, fall). Therefore, an accurate recognition of the context is paramount to provide the appropriate privacy level. This project will investigate techniques to recognise accurately these variables and it will validate them under different use case scenarios.
Expected Results:
Computer vision algorithms for continuous estimation of the context in which a person is video-monitored. These includes person recognition, appearance recognition, activity recognition, and event detection.
Supervisory Committee:
• Main Supervisor: Dr F. Flórez (University of Alicante)
• Second Supervisor: Dr J. Dinsmore (Trinity College Dublin)
• Co-Supervisor: Prof J.M. García (University of Alicante)
• Advisor: Dr E. Vazquez (Anyvision (NI) Ltd.), Dr R. Planinc (Cogvis)
Planned secondment(s):
• Secondment 1: Trinity College Dublin (Supervisor: Dr J Dinsmore), M18-M20, Training and research on healthcare applications
• Secondment 2: Anyvision (NI) Ltd. (Supervisor: Dr E. Vazquez), M32-M34: Training and research on video-based human activity and appearance recognition
Enrolment in Doctoral degree(s):
Doctoral Programme in Computer Science, University Institute for Computer Research, Universidad de Alicante
How to apply?
Submit your application to https://www.visuaal-itn.eu/esr-vacancies. Please, ensure that you select vacancy number ESR14.
Information:
For questions related to this project proposal, please contact [Email Address Removed]
For all other questions, please use the following email address, clearly indicating the visuAAL vacancy number ESR14: [Email Address Removed]
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