VIMES: A Wearable Memory Assistance System for Automatic Information Retrieval
Open accessAbstract
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).
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Location information and sudden changes in heart rate were connected to images taken using a wearable camera.
“For example, location information and sudden changes in heart rate were connected to images that were taken using a wearable camera (Wang & Tanaka, 2019; see also Bermejo et al., 2020).”
From Understanding Autobiographical Memory in the Digital Age: The AMEDIA-Model (2024) · cites this paper as Bermejo et al., 2020
The indexed passages contain bibliographic details and keywords for VIMES, but no description of location information or heart-rate changes being connected to wearable-camera images. Searches for those terms returned no passage addressing the claim. (LLM, conf=0.72)
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Do life-logging technologies support memory for the past?: an experimental study using sensecam
Sellen, A. J., Fogg, A., Aitken, M., Hodges, S., Rother, C., & Wood, K. (2007) · Proceedings of the SIGCHI Conference on Human Factors in Computing Systems · doi:10.1145/1240624.1240636 · Cited by 324 · see citing works
Browne, G., Berry, E., Kapur, N., Hodges, S., Smyth, G., Watson, P., & Wood, K. (2011) · Memory · doi:10.1080/09658211.2011.614622 · Cited by 92 · see citing works
Minimal memory for details in real life events
Misra, P., Marconi, A., Peterson, M., & Kreiman, G. (2018) · Scientific Reports · doi:10.1038/s41598-018-33792-2 · Cited by 39 · see citing works
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Understanding Autobiographical Memory in the Digital Age: The AMEDIA-Model
Hutmacher, F., Appel, M., & Schwan, S. (2024) · Psychological Inquiry · doi:10.1080/1047840x.2024.2384125 · Cited by 12 · see citing works
- Authors
- Bermejo, C., Braud, T., Yang, J., Mirjafari, S., Shi, B., Xiao, Y., & Hui, P.
- Affiliations
- Hong Kong University of Science and Technology (HK)
- Dartmouth College (US)
- Aalto University (FI)
- University of Helsinki (FI)
- Venue
- Proceedings of the 28th ACM International Conference on Multimedia
- Publisher
- ACM
- Published
- 2020-10-12
- Pages
- 3191-3200
- OpenAlex
- W3092760023
- Cited by
- 15
- References
- 3
- Citations by year
- 2025: 6 · 2024: 3 · 2023: 3 · 2021: 3
- FWCI
- 0.46
- Type
- conference paper
- Language
- en
- Open access
- green
- research.aalto.fi
- Locations
- ACM International Conference on Multimedia (ACM MM) (publishedVersion)
- Aaltodoc (Aalto University) (submittedVersion, other-oa)
- Työväentutkimus Vuosikirja (submittedVersion)
- Rare & Special e-Zone (The Hong Kong University of Science and Technology) (submittedVersion)
- Funders
- Research Grants Council of Hong Kongand the 5GEAR and FIT projects from Academy of Finland (16214817)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Augmented Reality Applications
- Physical Sciences › Computer Science › Human-Computer Interaction › Interactive and Immersive Displays
- Physical Sciences › Computer Science › Human-Computer Interaction › Virtual Reality Applications and Impacts
- Keywords
- augmented reality, smart glasses, wearable computing, event extraction, user study
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