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An Unsupervised Ensemble Approach for Emotional Scene Detection from Lifelog Videos

  • Hiroki NomiyaEmail author
  • Atsushi Morikuni
  • Teruhisa Hochin
Part of the Studies in Computational Intelligence book series (SCI, volume 569)

Abstract

An emotional scene detection method is proposed in order to retrieve impressive scenes from lifelog videos. The proposed method is based on facial expression recognition considering that a wide variety of facial expression could be observed in impressive scenes. Most of conventional facial expression techniques adopt supervised learning methods. This is a crucial problem because preparing sufficient training data requires considerable human effort due to the diversity of facial expressions observed in lifelog videos. We thus propose a more efficient emotional scene detection method using an unsupervised facial expression recognition on the basis of cluster ensembles. Our approach does not require any training data sets and is able to detect various emotional scenes. The detection performance of the proposed method is evaluated through an emotional scene detection experiment.

Keywords

Lifelog video retrieval facial expression recognition clustering ensemble learning 

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Hiroki Nomiya
    • 1
    Email author
  • Atsushi Morikuni
    • 1
  • Teruhisa Hochin
    • 1
  1. 1.Department of Information ScienceKyoto Institute of TechnologySakyo-kuJapan

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