Understanding presumption system from facial images

Atsushi Mimura, Masafumi Hagiwara

Research output: Contribution to conferencePaperpeer-review

Abstract

In this paper, we propose an understanding presumption system from facial images using a three-layered neural network. It can presume a degree of understanding from facial expressions; it can recognize whether a person understands a question or not. Feature points are located on each facial image and are used to extract an expression information. The expression information is given as an input and the system presumes the degree of understanding based on the facial images into 5 levels, from NOT UNDERSTAND to WELL UNDERSTAND. The network is learned using Back Propagation algorithm. The average presumption rates of the proposed system was 71.3%.

Original languageEnglish
Pages3270-3275
Number of pages6
Publication statusPublished - 1999 Dec 1
EventInternational Joint Conference on Neural Networks (IJCNN'99) - Washington, DC, USA
Duration: 1999 Jul 101999 Jul 16

Other

OtherInternational Joint Conference on Neural Networks (IJCNN'99)
CityWashington, DC, USA
Period99/7/1099/7/16

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence

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