Unsupervised Emotional Scene Detection from Lifelog Videos Using Cluster Ensembles

نویسندگان

  • Hiroki Nomiya
  • Atsushi Morikuni
  • Teruhisa Hochin
چکیده

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. Conventional facial expression techniques, which focus on discriminating typical facial expressions, will be inadequate for lifelog video retrieval because of the diversity of facial expressions. The authors thus propose a more flexible and efficient emotional scene detection method using an unsupervised facial expression recognition based on cluster ensembles. The authors’ approach does not need to predefine facial expressions and is able to detect emotional scenes containing a wide variety of facial expressions. The detection performance of the proposed method is evaluated through some emotional scene detection experiments. Unsupervised Emotional Scene Detection from Lifelog Videos Using Cluster Ensembles

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عنوان ژورنال:
  • IJSI

دوره 1  شماره 

صفحات  -

تاریخ انتشار 2013