Research Article
Structuring and Presenting Lifelogs Based on Location Data
@INPROCEEDINGS{10.1007/978-3-319-11564-1_14, author={Basel Kikhia and Andrey Boytsov and Josef Hallberg and Zaheer ul Hussain Sani and H\ae{}kan Jonsson and K\ae{}re Synnes}, title={Structuring and Presenting Lifelogs Based on Location Data}, proceedings={Pervasive Computing Paradigms for Mental Health. 4th International Symposium, MindCare 2014, Tokyo, Japan, May 8-9, 2014, Revised Selected Papers}, proceedings_a={MINDCARE}, year={2014}, month={12}, keywords={Activity recognition Activity inference Lifelogging Clustering algorithms DBSAN SenseCam GPS}, doi={10.1007/978-3-319-11564-1_14} }- Basel Kikhia
Andrey Boytsov
Josef Hallberg
Zaheer ul Hussain Sani
Håkan Jonsson
Kåre Synnes
Year: 2014
Structuring and Presenting Lifelogs Based on Location Data
MINDCARE
Springer
DOI: 10.1007/978-3-319-11564-1_14
Abstract
Lifelogging techniques help individuals to log their life and retrieve important events, memories and experiences. Structuring lifelogs is a major challenge in lifelogging systems since the system should present the logs in a concise and meaningful way to the user. In this paper the authors present an approach for structuring lifelogs as places and activities based on location data. The structured lifelogs are achieved using a combination of density-based clustering algorithms and convex hull construction to identify the places of interest. The periods of time where the user lingers at the same place are then identified as possible activities. In addition to structuring lifelogs the authors present an application in which images are associated to the structuring results and presented to the user for reviewing. The system is evaluated through a user study consisting of 12 users, who used the system for 1 day and then answered a survey. The proposed approach in this paper allows automatic inference of information about significant places and activities, which generates structured image-annotated logs of everyday life.