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Abstract
The advancement of artificial intelligence and wearable computing triggers the radical innovation of cognitive applications. In this work, we propose VIMES, an augmented reality-based memory assistance system that helps recall declarative memory, such as whom the user meets and what they chat. Through a collaborative method with 20 participants, we design VIMES, a system that runs on smartglasses, takes the first-person audio and video as input, and extracts personal profiles and event information to display on the embedded display or a smartphone. We perform an extensive evaluation with 50 participants to show the effectiveness of VIMES for memory recall. VIMES outperforms (90% memory accuracy) other traditional methods such as self-recall (34%) while offering the best memory experience (Vividness, Coherence, and Visual Perspective all score over 4/5). The user study results show that most participants find VIMES useful (3.75/5) and easy to use (3.46/5).
Original language | English |
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Title of host publication | Proceedings of the 28th ACM International Conference on Multimedia |
Publisher | ACM |
Pages | 3191-3200 |
Number of pages | 10 |
ISBN (Electronic) | 978-1-4503-7988-5 |
DOIs | |
Publication status | Published - Oct 2020 |
MoE publication type | A4 Conference publication |
Event | ACM International Conference on Multimedia - Virtual, Online Duration: 12 Oct 2020 → 16 Oct 2020 Conference number: 28 |
Conference
Conference | ACM International Conference on Multimedia |
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Abbreviated title | MM |
City | Virtual, Online |
Period | 12/10/2020 → 16/10/2020 |
Keywords
- information retrieval
- wearable computing
- memory assistance system
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- 1 Finished
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FIT: Federated probabilistic modelling for heterogeneous programmable IoT systems
Kaski, S. (Principal investigator)
04/09/2019 → 31/12/2022
Project: Academy of Finland: Other research funding