articleJan 1, 2007Closed access

Eyeblink-based Anti-Spoofing in Face Recognition from a Generic Webcamera

Zhejiang University · Omron (Japan)

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Abstract

We present a real-time liveness detection approach against photograph spoofing in face recognition, by recognizing spontaneous eyeblinks, which is a non-intrusive manner. The approach requires no extra hardware except for a generic webcamera. Eyeblink sequences often have a complex underlying structure. We formulate blink detection as inference in an undirected conditional graphical framework, and are able to learn a compact and efficient observation and transition potentials from data. For purpose of quick and accurate recognition of the blink behavior, eye closity, an easily-computed discriminative measure derived from the adaptive boosting algorithm, is developed, and then smoothly embedded into the…

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674
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Authors

4

Topics & keywords

Keywords
  • Liveness
  • Discriminative model
  • Computer science
  • AdaBoost
  • Spoofing attack
  • Artificial intelligence
  • Pattern recognition (psychology)
  • Boosting (machine learning)
UN Sustainable Development Goals
  • Reduced inequalities
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