Understanding presumption system from facial images

Atsushi Mimura, Masafumi Hagiwara

研究成果: Paper査読


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%.

出版ステータスPublished - 1999 12 1
イベントInternational Joint Conference on Neural Networks (IJCNN'99) - Washington, DC, USA
継続期間: 1999 7 101999 7 16


OtherInternational Joint Conference on Neural Networks (IJCNN'99)
CityWashington, DC, USA

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence

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