Advertisement

Integrating 3D Facial Model with Person-Centered Care Support System for People with Dementia

  • Shota NakataniEmail author
  • Sachio Saiki
  • Masahide Nakamura
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 722)

Abstract

Our research group has been studying a speech communication system with a virtual agent (VA), to support person-centered care (PCC) of people with dementia (PWD). The current system uses an unfamiliar avatar for the VA, which causes a limitation in the care effects. In this paper, we develop a novel system that dynamically creates a VA based on a given facial image. The proposed system constructs a three-dimensional model based on facial landmarks within the image. It then stretches and transforms some portions of the 3D model to generate facial expressions. From just a given picture, the proposed system easily generates a communication agent familiar with individual PWD. Hence, it can implement (virtual, but effective) conversations with familiar partners.

Keywords

Person-centered care Person with dementia Virtual agent 

References

  1. 1.
    Cabinet Office, Government of Japan: Annual report on the aging society (2017). http://www8.cao.go.jp/kourei/whitepaper/w-2017/html/zenbun/s1_1_1.html. Accessed June 2017
  2. 2.
    Tokunaga, S., Tamamizu, K., Saiki, S., Nakamura, M., Yasuda, K.: VirtualCareGiver: personalized smart elderly care. Int. J. Softw. Innov. (IJSI) 5(1), 30–43 (2016)CrossRefGoogle Scholar
  3. 3.
    Tamamizu, K., Sakakibara, S., Saiki, S., Nakamura, M., Yasuda, K.: Capturing activities of daily living for elderly at home based on environment change and speech dialog. In: International Conference on Digital Human Modeling 2017 (DHM 2017). LNCS, vol. 10287, pp. 183–194, July 2017Google Scholar
  4. 4.
    Sakakibara, S., Saiki, S., Nakamura, M., Yasuda, K.: Generating personalized dialogue towards daily counseling system for home dementia care. In: International Conference on Digital Human Modeling 2017 (DHM 2017). LNCS, vol. 10287, pp. 161–172, July 2017Google Scholar
  5. 5.
  6. 6.
  7. 7.
    Taigman, Y., Yang, M., Ranzato, M.A., Wolf, L.: DeepFace: closing the gap to human-level performance in face verification. In: CVPR 2014 (2014)Google Scholar
  8. 8.
    Fan, H., Cao, Z., Jiang, Y., Yin, Q., Doudou, C.: Learning deep face representation. arXiv:1403.2802
  9. 9.
    Zhang, Z., Luo, P., Loy, C.C., Tang, X.: Facial landmark detection by deep multi-task learning. In: European Conference on Computer Vision (2014)Google Scholar
  10. 10.
  11. 11.

Copyright information

© Springer International Publishing AG 2018

Authors and Affiliations

  • Shota Nakatani
    • 1
    Email author
  • Sachio Saiki
    • 1
  • Masahide Nakamura
    • 1
  1. 1.Graduate SchoolKobe UniversityKobeJapan

Personalised recommendations