바이모달 정보를 이용한 기절상황인식 시스템에 관한 연구

A Study on the Recognition System of Faint Situation based on Bimodal Information

  • 소인미 (원광대학교 컴퓨터공학과) ;
  • 정성태 (원광대학교 컴퓨터공학과)
  • 투고 : 2009.08.26
  • 심사 : 2009.09.29
  • 발행 : 2010.02.28

초록

본 논문은 카메라 영상 정보와 기울기 센서 정보를 통합한 바이모달 응급상황 인식방법을 제안한다. 제안된 방법은 어느 한 센서가 오작동 하거나 사용자가 착용형 기울기 센서를 착용하지 않거나, 영상 획득의 어려움이 있는 욕실과 같은 곳에 있는 경우에도 응급 상황을 감지하여 센서 간에 상호 협력과 보완을 함으로써 응급 상황을 인식할 수 있다. 본 논문에서는 HMM 학습 및 인식을 통해 걷는 동작, 바닥에 앉는 동작, 소파에 앉는 동작, 눕는 동작, 기절 동작을 판단할 수 있도록 하였다. 영상의 특징 벡터와 기울기 센서의 특징 벡터를 결합하여 학습하고 인식했을 때, 인식률의 향상을 가져올 수 있었다. 또한 다양한 조명의 변화에도 적응적 배경 모델을 통해 움직이는 객체를 강건하게 검출할 수 있어서 높은 인식률을 유지할 수 있었다.

This study proposes a method for the recognition of emergency situation according to the bimodal information of camera image sensor and gravity sensor. This method can recognize emergency condition by mutual cooperation and compensation between sensors even when one of the sensors malfunction, the user does not carry gravity sensor, or in the place like bathroom where it is hard to acquire camera images. This paper implemented HMM(Hidden Markov Model) based learning and recognition algorithm to recognize actions such as walking, sitting on floor, sitting at sofa, lying and fainting motions. Recognition rate was enhanced when image feature vectors and gravity feature vectors are combined in learning and recognition process. Also, this method maintains high recognition rate by detecting moving object through adaptive background model even in various illumination changes.

키워드

참고문헌

  1. I. Korhonen, J. Parkka, and M.V. Gils, "Health Monitoring in the Home of the Future," IEEE Engineering in Medicine and Biology Magazine, pp. 66-73, 2003.
  2. A. Fitzgibbon, M. Pilu, and R.B. Fisher, "Direct least square fitting of ellipses," IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol.21, No.5, pp. 476-480, 1999. https://doi.org/10.1109/34.765658
  3. S. Zimmermann and D. Kuban, "A video pan/tilt/magnify/rotate system with no moving parts," Proceedings of IEEE/AlA Digital Avionics Systems Conference, pp. 523-531, 1992.
  4. M.J. Gibson, R.O. Andres, B. Isaacs, T. Radebaugh, and J. Worm-Petersen, "The prevention of falls in later life : A report of the Kellogg International Work Group on the Prevention of Falls by the Elderly," Danish Medical Bulletin, 34 Supplement 4:1-24, 1987.
  5. J. Kimel and J. Lundell, "Long-term Deployments of Pervasive Technology into the Homes of Older Adults," Interactions, Vol. 14, No.4, pp. 38-41, 2007. https://doi.org/10.1145/1273961.1273983
  6. H. Nait-Charif and S. McKenna, "Activity summarisation and fall detection in a supportive home environment," In Proceedings of the 17th International Conference on Pattern Recognition(ICPR), Vol. 4, pp. 323-326, 2004.
  7. S.-G. Miaou, P.-H. Sung, and C.-Y. Huang, "A Customized Human Fall Detection System Using Omni-Camera Images and Personal Information," Proc. of Distributed Diagnosis and Home Healthcare(D2H2) Conference, pp. 39-42, 2006.
  8. M.-L. Wang, C.-C. Huang and H.-Y. Lin, "An Intelligent Surveillance System Based on an Omnidirectional Vision Senso," IEEE Conference on Cybernetics and Intelligent Systems, pp. 1-6, 2006.
  9. 소인미, 한대경, 강선경, 김영운, 정성태, "어안렌즈 카메라를 이용한 기절동작 인식," 한국컴퓨터정보학회논문지, Vol.13, No.4, pp. 97-103, 2008.
  10. 김영운, 강선경, 소인미, 한대경, 김윤진, 정성태, "멀티모달 정보를 이용한 응급상황 인식 시스템", 대한전자공학회 하계학술대회논문집, Vol.31, No.1, pp. 757-758, 2008.
  11. C. Stauffer and W.E.L. Grimson, "Adaptive background mixture models for real-time tracking," IEEE Computer Society Conference on Computer Vision and Pattern Recognition, pp. 246-252, 1999.
  12. R. Crane, A simplified approach to image processing, Prentice Hall, 1997.
  13. I. Pitas, Digital Image Processing schemes and Application, New York, John Wiley and Sons Inc., 2000.
  14. A. Fitzgibbon, M. Pilu, and R.B. Fisher, "Direct least square fitting of ellipses," IEEE Transactions on Pattern Analysis and Machine Intelligence, Vol.21, No.5, pp. 476-480, 1999. https://doi.org/10.1109/34.765658
  15. S. Zimmermann and D. Kuban, "A video pan/tilt/magnify/rotate system with no moving parts," Proceedings of IEEE/AlA Digital A vionics Systems Conference, pp. 523-531, 1992.