Organizing egocentric videos of daily living activities

Abstract

Egocentric videos are becoming popular since the possibility to observe the scene flow from the user’s point of view (First Person Vision). Among the different applications of egocentric vision is the daily living monitoring of a user wearing the camera. We propose a system able to automatically organize egocentric videos acquired by the user over different days. Through an unsupervised temporal segmentation, each egocentric video is divided in chapters by considering the visual content. The obtained video segments related to the different days are hence connected according to the scene context in which the user acts. Experiments on a challenging egocentric video dataset demonstrate the effectiveness of the proposed approach that outperforms with a good margin the state of the art in accuracy and computational time.