State of the Art of Audio- and Video-Based Solutions for AAL

Slavisa Aleksic, Michael Atanasov, Jean Calleja Agius, Kenneth Camilleri, Anto Cartolovni, Pau Climent-Peerez, Sara Colantonio, Stefania Cristina, Vladimir Despotovic, Hazim Kemal Ekenel, Ekrem Erakin, Francisco Florez-Revuelta, Danila Germanese, Nicole Grech, Steinunn Gróa Sigurðardóttir, Murat Emirzeoglu, Ivo Iliev, Mladjan Jovanovic, Martin Kampel, William KearnsAndrzej Klimczuk, Lambros Lambrinos, Jennifer Lumetzberger, Wiktor Mucha, Sophie Noiret, Zada Pajalic, Rodrigo Rodriguez Peerez, Galidiya Petrova, Sintija Petrovica, Peter Pocta, Angelica Poli, Mara Pudane, Susanna Spinsante, Albert Ali Salah, Maria Jose Santofimia, Anna Sigridur Islind, Lacramioara Stoicu-Tivadar, Hilda Tellioglu, Andrej Zgank

Research output: Working paperPreprint

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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.
Original languageUndefined/Unknown
DOIs
Publication statusPublished - 26 Jun 2022

Keywords

  • cs.CY
  • cs.AI
  • cs.HC
  • cs.SD
  • eess.AS
  • I.2

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