PT Unknown
AU Estefania Talavera
   Nicolai Petkov
   Petia Radeva
TI Unsupervised Routine Discovery in Egocentric Photo-Streams
BT 18th International Conference on Computer Analysis of Images and Patterns
PY 2019
BP 576
EP 588
VL 11678
DI 10.1007/978-3-030-29888-3_47
DE Routine discovery; Lifestyle; Egocentric vision; Behaviour analysis
AB The routine of a person is defined by the occurrence of activities throughout different days, and can directly affect the person’s health. In this work, we address the recognition of routine related days. To do so, we rely on egocentric images, which are recorded by a wearable camera and allow to monitor the life of the user from a first-person view perspective. We propose an unsupervised model that identifies routine related days, following an outlier detection approach. We test the proposed framework over a total of 72 days in the form of photo-streams covering around 2 weeks of the life of 5 different camera wearers. Our model achieves an average of 76% Accuracy and 68% Weighted F-Score for all the users. Thus, we show that our framework is able to recognise routine related days and opens the door to the understanding of the behaviour of people.
ER