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 language | English |
|---|---|
| Title of host publication | Wearable Sensors |
| Subtitle of host publication | Fundamentals, Implementation and Applications |
| Publisher | Elsevier |
| Pages | 415-433 |
| Number of pages | 19 |
| ISBN (Print) | 978-0-12-819246-7 |
| DOIs | |
| Publication status | Published - 1 Jan 2020 |
| Externally published | Yes |
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