Browsing personal images using episodic memory (time + location)

Authors:
Chufeng Chen;Michael Oakes;John Tait
Affiliations:
School of Computing and Technology, University of Sunderland;School of Computing and Technology, University of Sunderland;School of Computing and Technology, University of Sunderland
Venue:
ECIR'06 Proceedings of the 28th European conference on Advances in Information Retrieval
Year:
2006

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Abstract

In this paper we consider episodic memory for system design in image retrieval. Time and location are the main factors in episodic memory, and these types of data were combined for image event clustering. We conducted a user studies to compare five image browsing systems using searching time and user satisfaction as criteria for success. Our results showed that the browser which clusters images based on time and location data combined was significantly better than four other more standard browsers. This suggests that episodic memory is potentially useful for improving personal image management.