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Friendly Faces: Weakly Supervised Character Identification

  • Matthew Marter
  • Simon Hadfield
  • Richard Bowden
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8912)

Abstract

This paper demonstrates a novel method for automatically discovering and recognising characters in video without any labelled examples or user intervention. Instead weak supervision is obtained via a rough script-to-subtitle alignment. The technique uses pose invariant features, extracted from detected faces and clustered to form groups of co-occurring characters. Results show that with 9 characters, 29% of the closest exemplars are correctly identified, increasing to 50% as additional exemplars are considered.

Keywords

Linear Predictor Active Appearance Model Shot Boundary Facial Landmark Shot Boundary Detection 
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 International Publishing Switzerland 2015

Authors and Affiliations

  • Matthew Marter
    • 1
  • Simon Hadfield
    • 1
  • Richard Bowden
    • 1
  1. 1.CVSSPUniversity of SurreySurreyUK

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