KIPS Transactions on Computer and Communication Systems (정보처리학회논문지:컴퓨터 및 통신 시스템)

Korea Information Processing Society (한국정보처리학회)
권호 표지
DOI QR코드

DOI QR Code

Development of Kinect-Based Pose Recognition Model for Exercise Game

운동 게임을 위한 키넥트 센서 기반 운동 자세 인식 모델 개발

  • 박경신 (단국대학교 응용컴퓨터공학과)
  • Received : 2016.08.09
  • Accepted : 2016.08.29
  • Published : 2016.10.31
Download PDF
⟨ Previous Next ⟩

Abstract

Recently there has been growing popularity in exergame, such as Wii Sport or Xbox Fitness game, which enables users to get physical exercise while playing the games. In such experienced exercise games, the user's posture recognition is very important to find out exactly how much the users need to take their body posture as compared to the proper posture. This paper proposes a new exercise posture recognition model designed for the exercise game content for the elderly. The proposed model is based on extracting feature points of a skeleton model provided by the Kinect sensor to generate the feature vectors to recognize the user's exercise posture information. This paper describes the design and implementation of the exercise posture recognition model and demonstrates the feasibility of this proposed posture recognition model through a simple experiment. The experimental results showed 94.52% of average accordance rate for 12 exercise postures of 10 participants.

최근 Wii Sport나 Xbox Fitness 등 실제와 똑같이 몸을 움직이도록 하는 기능성 운동 게임인 엑서 게임이 인기를 끌고 있다. 그런데 이런 체감형 운동 게임에서는 사용자가 운동 자세를 얼마나 정확하게 취했는지 자세의 교정이 얼마나 필요한지를 알 수 있기 위하여 자세 인식이 크게 중요하다. 본 연구에서는 고령자를 대상으로 한 운동프로그램 콘텐츠에서 사용자의 자세 정보를 인식하기 위하여 키넥트 센서에서 제공하는 골격 모델의 특징점을 추출하여 각각의 특징벡터를 생성하여 만든 운동 자세 인식 모델 방법을 제안하였다. 본 논문에서는 제안하는 운동 자세 인식 모델의 설계 및 구현을 설명하였고, 간단한 실험을 통해서 제안된 운동 자세 인식 모델의 사용 가능성을 증명하였다. 실험결과 10명의 참여자들의 12가지 운동 자세에 대한 전체 평균은 94.52% 정도 일치율을 보였다.

Keywords

References

  1. Bum-Ro Lee, "A Development of Motion Detection Based Serious Game "ChoDeungGangHo" for Physical Training," Journal of the Korea Society of Computer and Information, Vol.20, No.11, pp.55-62, 2015.
  2. Eui-Young Kim, Changhoon Park, and Daegeun Kim, "A Study on Effectiveness and Preference of Tangible Fitness Game," Journal of Korea Game Society, Vol.12, No.1, pp.67-77, 2012.
  3. Young Soog Chae, "A Serious Game Design and Prototype Development for Rehabilitation using Kinect Tools," Journal of Korea Multimedia Society, Vol.17, No.2, pp.248-256, 2014. https://doi.org/10.9717/kmms.2014.17.2.248
  4. Daejun Kim and Changhoon Park, "Racing Track and Feedback for Adaptable Exercise Game," in Proceedings of Korean Game Society, pp.177-184, 2011.
  5. Jin-ho Ahn, Sejun Park, Jungdo Kim, Kyung Sik Kim, and Changhoon Park, "A She-Type Game Controller for Exergames," Journal of Korean Institute of Information Technology, Vol.7, No.6, pp.159-165, 2009.
  6. Jungwon Yoon, Sehwan Kim, Jeha Ruy, and Woontack Woo, "A Full Body Gumdo Game with an Intelligent Cyber Fencer using Multi-modal (3D Vision and Speech) Interface," KIISE Transactions on Computing Practices, Vol.9, No.4, pp.420-430, 2003.
  7. KyungSik Kim, YoonJung Lee, and SeongSuk Oh, "Development of Analysis of a Walking Game 'Paldokangsan3' Using Kinect", Journal of Korea Game Society, Vol.14, No.1, pp.49-58, 2014.
  8. Hye-jeong Yun, Kwang-il Kim, Jeong-hun Lee, and Hae-Yeoun Lee, "Development of Experience Dance Game using Kinect Motion Capture," KIPS Transactions on Software and Data Engineering, Vol.3, No.1, pp.49-56, 2014. https://doi.org/10.3745/KTSDE.2014.3.1.49
  9. Guan-Feng He, Jin-Woong Park, Sun-Kyung Kand, and Sung-Tae Jung, "Development of Gesture Recognition-Based 3D Serious Games," Journal of Korea Game Society, Vol.11, No.6, pp.103-114, 2011.
  10. Han Suk Choi, "Kinect-based Motion Recognition Model for the 3D Contents Control," Journal of the Korea Contents Association, Vol.14, No.1, pp.24-29, 2014.
  11. Sungyoung Cho, Hyeran Byun, Hee Kyung Lee, and Jihun Cha, "Arm Gesture Recognition for Shooting Games based on Kinect Sensor," Journal of KIISE: Software and Applications, Vol.39, No.10, pp.796-805, 2012.