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Browsing Personal Images Using Episodic Memory (Time + Location)

  • Chufeng Chen
  • Michael Oakes
  • John Tait
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3936)

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.

Keywords

Global Position System Episodic Memory Image Retrieval Location Cluster Machine Place 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Chufeng Chen
    • 1
  • Michael Oakes
    • 1
  • John Tait
    • 1
  1. 1.School of Computing and TechnologyUniversity of SunderlandUK

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