Serious Games Application for Memory Training Using Egocentric Images

Gabriel de Oliveira, Marc Bolanos, Estefanía Talavera Martínez, Olga Gelonch, Maite Garolera

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

1 Citation (Scopus)
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Abstract

Mild cognitive impairment is the early stage of several neurodegenerative diseases, such as Alzheimer's. In this work, we address the use of lifelogging as a tool to obtain pictures from a patient's daily life from an egocentric point of view. We propose to use them in combination with serious games as a way to provide a non-pharmacological treatment to improve their quality of life. To do so, we introduce a novel computer vision technique that classifies rich and non rich egocentric images and uses them in serious games. We present results over a dataset composed by 10,997 images, recorded by 7 different users, achieving 79\% of F1-score. Our model presents the first method used for automatic egocentric images selection applicable to serious games.
Original languageEnglish
Title of host publicationICIAP 2017 - New Trends in Image Analysis and Processing
PublisherSpringer
Pages120-130
Number of pages12
Publication statusPublished - Dec-2017
EventWorkshop on Social Signal Processing and Beyond: sspandbe - Catania, Catania, Italy
Duration: 11-Sept-2017 → …

Conference

ConferenceWorkshop on Social Signal Processing and Beyond
Country/TerritoryItaly
CityCatania
Period11/09/2017 → …

Keywords

  • lifelogging
  • machine learning
  • serious games
  • egocentric vision
  • mild cognitive impairment
  • computer vision

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