한국전자통신학회논문지 (The Journal of the Korea institute of electronic communication sciences)

한국전자통신학회 (Korea Institute of Electronic Communication Science)
권호 표지
DOI QR코드

DOI QR Code

YOLO알고리즘을 활용한 시각장애인용 식사보조 시스템 개발

Development a Meal Support System for the Visually Impaired Using YOLO Algorithm

  • 투고 : 2021.08.25
  • 심사 : 2021.10.17
  • 발행 : 2021.10.31
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

시각이 온전한 사람들은 식사를 할 때 시각에 대한 의존도를 깊게 인지하지 못한다. 그러나 시각장애인은 식단에 어떤 음식이 있는지 알지 못하기 때문에 옆에 있는 보조인이 시각장애인 수저로 음식의 위치를 시계방향 또는 전후좌우 등 일정한 방향으로 설명하여 그릇 위치를 확인한다. 본 논문에서는 시각장애인이 스마트폰의 카메라를 이용하여 자신의 식단을 비추면 각각의 음식 이미지를 인식하여 음성으로 음식의 이름을 알려주는 식사보조 시스템의 개발 내용에 대해 기술한다. 이 시스템은 음식과 식기도구(숟가락)의 이미지를 학습한 YOLO모델을 통해 숟가락이 놓인 음식을 추출해 내고, 이 음식이 무엇인지를 인식하여 이를 음성으로 알려준다. 본 시스템을 통해 시각장애인은 식사보조인의 도움없이 식사를 할 수 있음으로써 자립의지와 만족도를 높일 수 있을 것으로 기대한다.

Normal people are not deeply aware of their dependence on sight when eating. However, since the visually impaired do not know what kind of food is on the table, the assistant next to them holds the blind spoon and explains the position of the food in a clockwise direction, front and rear, left and right, etc. In this paper, we describe the development of a meal assistance system that recognizes each food image and announces the name of the food by voice when a visually impaired person looks at their table using a smartphone camera. This system extracts the food on which the spoon is placed through the YOLO model that has learned the image of food and tableware (spoon), recognizes what the food is, and notifies it by voice. Through this system, it is expected that the visually impaired will be able to eat without the help of a meal assistant, thereby increasing their self-reliance and satisfaction.

키워드

과제정보

본 연구는 2021년 과학기술정보통신부 및 정보통신기획평가원의 SW중심대학사업의 연구결과로 수행되었음(2019-0-01817)

참고문헌

  1. Korean Consumer Agency, "Investigation of the Safety Status of Walking for the Visually Impaired," Safety Report, Feb. 2021. pp.1-27.
  2. C. Ban, D. H. Kim, and B. Choi, "Design and Implementation of Order Settlement System Using Artificial Intelligence Speaker," J. of The Korea Institute of Electronic Communication Sciences, vol. 14, no. 6, 2019, pp. 1181-1186. https://doi.org/10.13067/JKIECS.2019.14.6.1181
  3. Y. Han, J. Sim, G. Kim, H. Lee, and J. Sin, "Walking Assistance Device for Prevention of Accidents of Visually Impaired People," J. of The Korea Institute of Electronic Communication Sciences, vol. 14, no. 6, 2019, pp. 1241-1248. https://doi.org/10.13067/JKIECS.2019.14.6.1241
  4. B. Liyuan and P. Younghuan."Application research on dining experiences of visually impaired users based on FAST method," In Proc. of Ergonomics Society of Korea, Oct. 2020. pp.99-103.
  5. W.-S. Lee, S.-Y. Park, and K.-H. Ye, "A Study on the Quality of Life depending on the Degree of Visual Impairment - With Activities of Daily Living and Instrumental Activities of Daily Living," J. of Korean Ophthalmic Optics Society, vol. 23, no. 3, Sep. 2018. pp.203-212. https://doi.org/10.14479/jkoos.2018.23.3.203
  6. S. ark, alvanov, C. ee, N. Jeong, Y. ho, and H. Je, "The development of food image detection and recognition model of Korean food for mobile dietary management," Nutrition Research and Practice, vol. 13, no. 6, Dec. 2019, pp. 521-528. https://doi.org/10.4162/nrp.2019.13.6.521
  7. S. Lee, E. Hong, and J.Lee, "Deep Learning Technology for Smart Diet Management," Kakao Enterprise, TECH&, Oct. 2020.
  8. S. Ruder, "An overview of gradient descent optimization algorithms", arXiv preprint arXiv:1609.04747, 2016.
  9. S. ee and M. ang, "Implementation of Object Detection and Voice Guidance System for The Visually Handicapped using Object Recognition Technology," J. of the Institute of Electronics and Information Engineers, vol. 55, no. 11, Nov. 2018, pp. 65-71. https://doi.org/10.5573/ieie.2018.55.11.65
  10. J. oo, D. an, C. Yr, and U. h, "YOLO-based Walking Assistance Application for Blind People," Proc. of the Korean Information Science Society Conference Research and Practice, Jeju, Korea, June 2019, pp. 1776-1778.