Validating the Detection of Everyday Concepts in Visual Lifelogs D. Byrne, A. R. Doherty, C. G. M. Snoek, G. J. F. Jones, A. F. Smeaton In International Conference on Semantic and Digital Media Technologies 2008. [bibtex] [pdf] [url]

The Microsoft SenseCam is a small lightweight wearable camera used to passively capture photos and other sensor readings from a user’s day-to-day activities. It can capture up to 3,000 images per day, equating to almost 1 million images per year. It is used to aid memory by creating a personal multimedia lifelog, or visual recording of the wearer’s life. However the sheer volume of image data captured within a visual lifelog creates a number of challenges, particularly for locating relevant content. Within this work, we explore the applicability of semantic concept detection, a method often used within video retrieval, on the novel domain of visual lifelogs. A concept detector models the correspondence between low-level visual features and high-level semantic concepts (such as indoors, outdoors, people, buildings, etc.) using supervised machine learning. By doing so it determines the probability of a concept’s presence. We apply detection of 27 everyday semantic concepts on a lifelog collection composed of 257,518 SenseCam images from 5 users. The results were then evaluated on a subset of 95,907 images, to determine the precision for detection of each semantic concept and to draw some interesting inferences on the lifestyles of those 5 users. We additionally present future applications of concept detection within the domain of lifelogging.

@InProceedings{ByrneICSDMT2008,
  author       = "Byrne, D. and Doherty, A. R. and Snoek, C. G. M. and Jones, G. J. F.
                  and Smeaton, A. F.",
  title        = "Validating the Detection of Everyday Concepts in Visual Lifelogs",
  booktitle    = "International Conference on Semantic and Digital Media Technologies",
  pages        = "15--30",
  year         = "2008",
  url          = "https://ivi.fnwi.uva.nl/isis/publications/2008/ByrneICSDMT2008",
  pdf          = "https://ivi.fnwi.uva.nl/isis/publications/2008/ByrneICSDMT2008/ByrneICSDMT2008.pdf",
  has_image    = 1
}