Egocentric vision IT technologies for Alzheimer disease assessment and studies
Hugo Boujut (LaBRI), Vincent Buso (LaBRI), Guillaume Bourmaud (IMS),, Jenny Benois-Pineau (LaBRI), R\'emi M\'egret (IMS), Jean-Philippe Domenger, (LaBRI), Yann Ga\"estel (ISPED), Jean-Fran\c{c}ois Dartigues

TL;DR
This paper explores egocentric vision technology using wearable cameras to monitor activities and assess Alzheimer’s disease impact, focusing on location and saliency estimation modules.
Contribution
It introduces the development of egocentric vision tools specifically designed for clinical evaluation of dementia patients.
Findings
Development of automatic location estimation module
Implementation of visual saliency estimation for content interpretation
Potential for improved clinical assessment tools
Abstract
Egocentric vision technology consists in capturing the actions of persons from their own visual point of view using wearable camera sensors. We apply this new paradigm to instrumental activities monitoring with the objective of providing new tools for the clinical evaluation of the impact of the disease on persons with dementia. In this paper, we introduce the current state of the development of this technology and focus on two technology modules: automatic location estimation and visual saliency estimation for content interpretation.
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Taxonomy
TopicsVisual Attention and Saliency Detection · Advanced Image and Video Retrieval Techniques · Gaze Tracking and Assistive Technology
