Abstract
With an aging population that continues to grow, dementia is a major global health concern. It is a syndrome in which there is a deterioration in memory, thinking, behavior
and the ability to perform activities of daily living. Depression and aggressive behavior are the most upsetting and challenging symptoms of dementia. Automatic recognition of these behaviors would not only be useful to alert family members and caregivers, but also helpful in planning and managing daily activities of people with dementia (PwD). In this work, we propose a vision-based approach that unifies transfer learning and deep convolutional neural network (CNN) for the effective recognition of behavioral symptoms. We also compare the performance of state-of-the-art CNN features with the hand-crafted HOG-feature, as well as their combination using a basic linear SVM. The proposed method is evaluated on a newly created dataset, which is based on the dementia storyline in ITVs Emmerdale episodes. The Alzheimer’s Society has described it as a “realistic
portrayal” of the condition to raise awareness of the issues surrounding dementia.
Original language | English |
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Pages (from-to) | 1-6 |
Journal | 2018 15th IEEE International Conference on Advanced Video and Signal-based Surveillance (AVSS) Proceedigs |
Early online date | 14 Feb 2019 |
DOIs | |
Publication status | E-pub ahead of print - 14 Feb 2019 |
Keywords
- Aggressive and depressive behavior recognition
- Human-robot social interactions
- Assistive technology for dementia
- Health and social care
- Video analysis and recognition
- Transfer learning
- Deep learning
- CNN features
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Robbie the Robot for monitoring and caring people with dementia
BEHERA, A. (Participant)
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