Egocentric vision for lifestyle understanding

Estefania Talavera, Nicolai Petkov, Petia Radeva

Research output: Chapter in Book/Report/Conference proceedingChapterAcademicpeer-review

Abstract

Describing people’s lives has become a hot topic in several disciplines. Lifelogging appeared in the 1960s as the process of recording and tracking personal activity data generated by the daily behavior of a person. The development of new wearable technologies allows to automatically record data from our daily living. Wearable devices are lightweight and affordable, which shows potential for the increase of their use by our society. Egocentric images are recorded by wearable cameras and show a first-person view of the life of the camera wearer. These collected images show an objective view of the daily life of a person and thus are a rich source of information about his/her habits. However, there is a lack of tools for the analysis of collections of egocentric photo-sequences. This document investigates the development of automatic tools for the analysis of egocentric images with the ultimate goal of getting understanding of the lifestyle of wearable camera users.

Original languageEnglish
Title of host publicationWearable Sensors
Subtitle of host publicationFundamentals, Implementation and Applications
PublisherElsevier
Pages415-433
Number of pages19
ISBN (Print)978-0-12-819246-7
DOIs
Publication statusPublished - 1 Jan 2020
Externally publishedYes

Keywords

  • Behavior analysis
  • Egocentric vision
  • Food-scenes classification
  • Lifestyle tracking
  • Reality mining
  • Routine discovery
  • Sentiment retrieval
  • Social patterns
  • Temporal segmentation
  • Visual pattern recognition
  • Wearable cameras
  • n/a OA procedure

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