Conference Proceedings


Cathal Gurrin
Rashmi Gupta


Computer Science

eventsegmentation informationretrievalsystem featureextraction visual lifelog memoryaugmentation academic research lifelog lifelogging

Approaches for event segmentation of visual lifelog data (2018)

Abstract A personal visual lifelog can be considered to be a human memory augmentation tool and in recent years we have noticed an increased interest in the topic of lifelogging both in academic research and from industry practitioners. In this preliminary work, we explore the concept of event segmentation of visual lifelog data. Lifelog data, by its nature is continual and streams of multimodal data can easy run into thousands of wearable camera images per day, along with a significant number of other sensor sources. In this paper, we present two new approaches to event segmentation and compare them against pre-existing approaches in a user experiment with ten users. We show that our approaches based on visual concepts occurrence and image categorization perform better than the pre-existing approaches. We finalize the paper with a suggestion for next steps for the research community.
Collections Ireland -> Dublin City University -> Publication Type = Conference or Workshop Item
Ireland -> Dublin City University -> DCU Faculties and Centres = DCU Faculties and Schools: Faculty of Engineering and Computing: School of Computing
Ireland -> Dublin City University -> Status = Published
Ireland -> Dublin City University -> Subject = Computer Science: Lifelog
Ireland -> Dublin City University -> DCU Faculties and Centres = Research Initiatives and Centres: INSIGHT Centre for Data Analytics

Full list of authors on original publication

Cathal Gurrin, Rashmi Gupta

Experts in our system

Cathal Gurrin
Dublin City University
Total Publications: 206
Rashmi Gupta
Dublin City University
Total Publications: 5