Korean Journal of Computational Design and Engineering (한국CDE학회논문집)

Society for Computational Design and Engineering (한국CDE학회)
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Development of a Bicycle Fitting System Based on Depth Camera through Body Part Recognition

인체부위 인식을 통한 깊이 카메라 기반의 자전거 피팅 시스템 개발

  • Jeon, Hyesung (Dept. of Industrial Engineering, Ajou University) ;
  • Lee, Jinwon (Dept. of Industrial Engineering, Ajou University) ;
  • Yang, Jeongsam (Dept. of Industrial Engineering, Ajou University)
  • Received : 2015.06.24
  • Accepted : 2015.08.12
  • Published : 2015.12.01
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Abstract

Recently, there has been a gradual increase in the number of people who are interested in cycling, leading to an increasing number of cycling equipment consumers. However, many bicyclists get hurt because of their lack of knowledge about the right size of bicycle for their body. Although it is necessary for a rider to fit their bicycle to prevent injury, they reject a fitting service because of the long hours and high cost. In this study, we propose a bicycle fitting system that uses a depth camera to improve the limitations of existing manual fitting systems. With the defined formula, the system calculates the size of the bicycle using body image information extracted by a depth camera and visualizes a customized bicycle for a specific consumer. This system will not only save the customer time and money, but will prevent injury from the use of a bicycle that does not fit.

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References

  1. Ministry of Security and Public Administration, 2014, Statistical Yearbook of Security and Public Service, MOSPA, Daejeon, pp.306.
  2. Christiaans, H.H. and Bremner, A., 1998, Comfort on Bicycles and The Validity of a Commercial Bicycle Fitting System, Applied Ergonomics, 29(3), pp.201-211. https://doi.org/10.1016/S0003-6870(97)00052-5
  3. Baker, A., 2009, Bike Fit, 1820 Washington Place San Diego CA, pp.13-27.
  4. Silberman, M.R., Webner, D., Collina, S. and Shiple, B.J., 2005, Road Bicycle Fit, Clinical Journal of Sport Medicine, 15(4), pp.271-276. https://doi.org/10.1097/01.jsm.0000171255.70156.da
  5. Mestdagh, K., 1998, Personal Perspective: In Search of an Optimum Cycling Posture, Applied Ergonomics, 29(5), pp.325-334. https://doi.org/10.1016/S0003-6870(97)00080-X
  6. Ricard, M.D., Hills-Meyer, P., Miller, M.G. and Michael, T.J., 2006, The Effects of Bicycle Frame Geometry on Muscle Activation and Power During a Wingate Anaerobic Test, Journal of Sports Science & Medicine, 5(1), pp.25-32.
  7. Macdermid, P.W. and Edwards, A.M., 2010, Influence of Crank Length on Cycle Ergometry Performance of Well-Trained Female Cross- Country Mountain Bike Athletes, European Journal of Applied Physiology, 108(1), pp.177-182. https://doi.org/10.1007/s00421-009-1197-0
  8. Matsumoto, S., Tokuyasu, T. and Ohba, K., 2009, A Study on Postural Optimization for Bicycle Exercise Based on Electromyography, Artificial Life and Robotics, 14(2), pp.144-149. https://doi.org/10.1007/s10015-009-0642-9
  9. Piccardi, M., 2004, Background Subtraction Techniques: A Review, Proceedings of the IEEE International Conference on Systems, Man and Cybernetics, pp.3099-3104.
  10. Jeges, E., Kispal, I. and Hornak, Z., 2008, Measuring Human Height Using Calibrated Cameras, Proceedings of the IEEE International Conference on Human System Interactions, pp.755-760.
  11. Martin, C.C., Burkert, D.C., Choi, K.R., Wieczorek, N.B., McGregor, P.M., Herrmann, R.A. and Beling, P.A., 2012, A Real-Time Ergonomic Monitoring System Using the Microsoft Kinect, Proceedings of the IEEE Systems and Information Engineering Design Symposium, pp.50-55.
  12. Lee, J.W., Han, J.H. and Yang, J., 2014, Depth Camera-Based Posture Discrimination and Motion Interpolation for Real-Time Human Simulation, Transactions of the Society of CAD/CAM Engineers, 19(1), pp.68-79. https://doi.org/10.7315/CADCAM.2014.068
  13. Weiss, A., Hirshberg, D. and Black, M.J., 2011, Home 3D Body Scans from Noisy Image and Range Data, Proceedings of the IEEE International Conference in Computer Vision, pp.1951-1958.
  14. Anguelov, D., Srinivasan, P., Koller, D., Thrun, S., Rodgers, J. and Davis, J., 2005, Scape: Shape Completion and Animation of People, ACM Transactions on Graphics, 24(3), pp.408-416. https://doi.org/10.1145/1073204.1073207
  15. Dao, N.L., Deng, T. and Cai, J., 2014, Fast and Automatic Body Circular Measurement Based on A Single Kinect, Proceedings of the Asia-Pacific Signal and Information Processing Association, pp.1-4.
  16. Yeon, S.H. and Yoon, D.H., 2013, Implementation of Intellectual Smart Sizing and Fitting System for Bike User, Journal of the Korea Contents Association, 13(5), pp.451-458. https://doi.org/10.5392/JKCA.2013.13.05.451
  17. Competitive Cyclist Fit, http://www.competitivecyclist.com/Store/catalog/fitCalculatorBike.jsp.
  18. WrenchScience, http://www.wrenchscience.com.