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Quick Browsing of Shared Experience Videos Based on Conversational Field Detection

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Mobile Computing, Applications, and Services (MobiCASE 2018)

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Abstract

We propose a system to aid the browsing of shared experience data that includes multiple first-person view videos. Using this system, users can avoid the tedious task of searching through lengthy videos. Our system aids browsing by displaying situational information cues on the video seek-bar, and visualizing node graphs showing members participating in the scenes and their approximate location. Users of our system can search and browse events with the help of cues indicating participant names and their locations. We use auditory similarity to detect conversational fields in order to detect the dynamics of groups in crowded areas. We conduct an experiment to evaluate the ability of our system to decrease the time needed for finding specified scenes in lifelog videos. Our experimental results suggest that our system can aid the browsing of videos that include one’s own experiences, but cannot be proven to aid the browsing of unfamiliar data.

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Authors and Affiliations

  1. Future University Hakodate, Hokkaido, Japan

    Kai Toyama & Yasuyuki Sumi

Authors
  1. Kai Toyama
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  2. Yasuyuki Sumi
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Correspondence to Kai Toyama .

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Editors and Affiliations

  1. Ritsumeikan University, Kusatsu-shi, Shiga, Japan

    Kazuya Murao

  2. Toyohashi University of Technology, Toyohashi-shi, Aichi, Japan

    Ren Ohmura

  3. Kyushu Institute of Technology, Kitakyushu-shi, Fukuoka, Japan

    Sozo Inoue

  4. Okayama University, Okayama-shi, Okayama, Japan

    Yusuke Gotoh

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© 2018 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Toyama, K., Sumi, Y. (2018). Quick Browsing of Shared Experience Videos Based on Conversational Field Detection. In: Murao, K., Ohmura, R., Inoue, S., Gotoh, Y. (eds) Mobile Computing, Applications, and Services. MobiCASE 2018. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 240. Springer, Cham. https://doi.org/10.1007/978-3-319-90740-6_3

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  • DOI: https://doi.org/10.1007/978-3-319-90740-6_3

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-90739-0

  • Online ISBN: 978-3-319-90740-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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