State of the Art of Audio- and Video-Based Solutions for AAL
Computers and Society
2022-07-06 v2 Artificial Intelligence
Human-Computer Interaction
Sound
Audio and Speech Processing
Abstract
The report illustrates the state of the art of the most successful AAL applications and functions based on audio and video data, namely (i) lifelogging and self-monitoring, (ii) remote monitoring of vital signs, (iii) emotional state recognition, (iv) food intake monitoring, activity and behaviour recognition, (v) activity and personal assistance, (vi) gesture recognition, (vii) fall detection and prevention, (viii) mobility assessment and frailty recognition, and (ix) cognitive and motor rehabilitation. For these application scenarios, the report illustrates the state of play in terms of scientific advances, available products and research project. The open challenges are also highlighted.
Keywords
Cite
@article{arxiv.2207.01487,
title = {State of the Art of Audio- and Video-Based Solutions for AAL},
author = {Slavisa Aleksic and Michael Atanasov and Jean Calleja Agius and Kenneth Camilleri and Anto Cartolovni and Pau Climent-Peerez and Sara Colantonio and Stefania Cristina and Vladimir Despotovic and Hazim Kemal Ekenel and Ekrem Erakin and Francisco Florez-Revuelta and Danila Germanese and Nicole Grech and Steinunn Gróa Sigurðardóttir and Murat Emirzeoglu and Ivo Iliev and Mladjan Jovanovic and Martin Kampel and William Kearns and Andrzej Klimczuk and Lambros Lambrinos and Jennifer Lumetzberger and Wiktor Mucha and Sophie Noiret and Zada Pajalic and Rodrigo Rodriguez Peerez and Galidiya Petrova and Sintija Petrovica and Peter Pocta and Angelica Poli and Mara Pudane and Susanna Spinsante and Albert Ali Salah and Maria Jose Santofimia and Anna Sigridur Islind and Lacramioara Stoicu-Tivadar and Hilda Tellioglu and Andrej Zgank},
journal= {arXiv preprint arXiv:2207.01487},
year = {2022}
}