Resumen de Lifestyle understanding through the analysis of egocentric photo-streams
Estefanía Talavera Martínez
Describing people's lives has become a hot topic in several disciplines.
Lifelogging appeared in the 1960s as the process of recording a nd tracking personal activity data generated by the daily behaviour of a person. The development of new wearable technologies allows to automatically record data from our daily living. Wearable devices are light-ware 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 lack of tools for the analysis of collections of egocentric photo-sequences and thus room for progress.
My project will investigate the development of automatic tools for the analysis of egocentric images with the ultimate goal of getting understanding of the lifestyle of the camera wearer. We plan to address five main topics in the field of egocentric vision: Temporal photo-sequences segmentation, Routine discovery, Food-related scenes recognition, Sentiment retrieval, Social pattern characterization.
We hypothesise that the future developed automatic algorithms for the analysis of egocentric images will allow a better understanding of the lifestyle of the camera wearer. Applications based on the analysis of this data can lead to the improvement of the quality of life of people and therefore, are worth to continue exploring.
