Automatically assisting human memory: A SenseCam browser
Abstract
SenseCams have many potential applications as tools for lifelogging, including the possibility of use as a memory rehabilitation tool. Given that a SenseCam can log hundreds of thousands of images per year, it is critical that these be presented to the viewer in a manner that supports the aims of memory rehabilitation. In this article we report a software browser constructed with the aim of using the characteristics of memory to organise SenseCam images into a form that makes the wealth of information stored on SenseCam more accessible. To enable a large amount of visual information to be easily and quickly assimilated by a user, we apply a series of automatic content analysis techniques to structure the images into "events", suggest their relative importance, and select representative images for each. This minimises effort when browsing and searching. We provide anecdotes on use of such a system and emphasise the need for SenseCam images to be meaningfully sorted using such a browser.
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Wearable cameras have the advantage of monitoring behaviors through a first-person perspective in free-living conditions.
“Such cameras have the advantage of monitoring behaviors through a first-person perspective in free-living conditions [26,27]”
From Using Wearable Cameras to Categorize the Type and Context of Screen-Based Behaviors Among Adolescents: Observational Study (2022) · cites this paper as [26]
Data processing and coding times are limiting factors and may be unsuitable for use in large-scale studies, unless an automatic recognition algorithm is developed to classify different aspects of human behavior.
“In addition to coding issues, the data processing and coding times are limiting factors and may be unsuitable for use in large-scale studies, unless an automatic recognition algorithm is developed to classify different aspects of human behavior [26].”
From Using Wearable Cameras to Categorize the Type and Context of Screen-Based Behaviors Among Adolescents: Observational Study (2022) · cites this paper as [26]
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- Authors
- Doherty, A. R., Moulin, C. J. A., & Smeaton, A. F.
- Affiliations
- Clarity Centre for Sensor Web Technologies (IE)
- University of Leeds (GB)
- Corresponding author
- Doherty, Aiden R.
- Venue
- Memory
- Publisher
- Informa UK Limited
- Published
- 2011-10
- Volume
- 19
- Issue
- 7
- Pages
- 785-795
- ISSN
- 0965-8211 (ISSN-L)
- 1464-0686
- OpenAlex
- W2139541350
- Cited by
- 109
- References
- 27
- Citations by year
- 2026: 2 · 2025: 4 · 2024: 11 · 2023: 1 · 2022: 2 · 2021: 4 · 2020: 5 · 2019: 8 · 2018: 8 · 2017: 8 · 2016: 9 · 2015: 9 · 2014: 16 · 2013: 14 · 2012: 7
- FWCI
- 8.16
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Memory (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Video Analysis and Summarization
- Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Image Retrieval and Classification Techniques
- Social Sciences › Decision Sciences › Information Systems and Management › Personal Information Management and User Behavior
- Keywords
- SenseCam, lifelogging, memory rehabilitation, automatic content analysis, event detection, visual memory, assistive technology
- MeSH terms
- Automation, Cues, Environmental Monitoring, Humans, Image Processing, Computer-Assisted, Microcomputers, Photography, Mental Recall, Self-Help Devices, Software, User-Computer Interface, Information Storage and Retrieval, Patient Satisfaction, Search Engine, Memory, Episodic
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