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Effective real-time identification using Bayesian statistical methods gaze Network

베이지안 통계적 방안 네트워크를 이용한 효과적인 실시간 시선 식별

  • Received : 2016.02.12
  • Accepted : 2016.03.24
  • Published : 2016.03.31

Abstract

In this paper, we propose a GRNN(: Generalized Regression Neural Network) algorithms for new eyes and face recognition identification system to solve the points that need corrective action in accordance with the existing problems of facial movements gaze upon it difficult to identify the user and. Using a Kalman filter structural information elements of a face feature to determine the authenticity of the face was estimated future location using the location information of the current head and the treatment time is relatively fast horizontal and vertical elements of the face using a histogram analysis the detected. And the light obtained by configuring the infrared illuminator pupil effects in real-time detection of the pupil, the pupil tracking was - to extract the text print vector.

Keywords

Bayesian;Neural Networks;Kalman Filter;Real-Time

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