Author(s):

  • Bolanos, Marc
  • Dimiccoli, Mariella
  • Radeva, Petia

Abstract:

Visual lifelogging consists of acquiring images that capture the daily experiences of the user by wearing a camera over a long period of time. The pictures taken offer considerable potential for knowledge mining concerning how people live their lives; hence, they open up new opportunities for many potential applications in fields including healthcare, security, leisure, and the quantified self. However, automatically building a story from a huge collection of unstructured egocentric data presents major challenges. This paper provides a thorough review of advances made so far in egocentric data analysis and, in view of the current state of the art, indicates new lines of research to move us toward storytelling from visual lifelogging.

Document:

https://doi.org/10.1109/THMS.2016.2616296

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