Development of a Bicycle Fitting System Based on Depth Camera through Body Part Recognition

Received 24 June 2015; received in revised form 16 July 2015; accepted 12 August 2015ABSTRACT Recently, there has been a gradual increase in the number of people who are interested incycling, leading to an increasing number of cycling equipment consumers. However, many bicy-clists 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 ser-vice because of the long hours and high cost. In this study, we propose a bicycle fitting systemthat uses a depth camera to improve the limitations of existing manual fitting systems. With thedefined formula, the system calculates the size of the bicycle using body image informationextracted by a depth camera and visualizes a customized bicycle for a specific consumer. Thissystem will not only save the customer time and money, but will prevent injury from the use ofa bicycle that does not fit.Key Words: Bicycle fitting, Depth camera, Image processing, Parametric modeling

[1]  Dal-Hwan Yoon,et al.  Implementation of Intellectual Smart Sizing and Fitting System for Bike User , 2013 .

[2]  E. Jeges,et al.  Measuring human height using calibrated cameras , 2008, 2008 Conference on Human System Interactions.

[3]  Massimo Piccardi,et al.  Background subtraction techniques: a review , 2004, 2004 IEEE International Conference on Systems, Man and Cybernetics (IEEE Cat. No.04CH37583).

[5]  Sebastian Thrun,et al.  SCAPE: shape completion and animation of people , 2005, SIGGRAPH 2005.

[6]  Marc R Silberman,et al.  Road Bicycle Fit , 2005, Clinical journal of sport medicine : official journal of the Canadian Academy of Sport Medicine.

[7]  Michael J. Black,et al.  Home 3D body scans from noisy image and range data , 2011, 2011 International Conference on Computer Vision.

[8]  Michael G. Miller,et al.  The effects of bicycle frame geometry on muscle activation and power during a wingate anaerobic test. , 2006, Journal of sports science & medicine.

[9]  Shimpei Matsumoto,et al.  A study on postural optimization for bicycle exercise based on electromyography , 2009, Artificial Life and Robotics.

[10]  A. Edwards,et al.  Influence of crank length on cycle ergometry performance of well-trained female cross-country mountain bike athletes , 2009, European Journal of Applied Physiology.

[11]  H H Christiaans,et al.  Comfort on bicycles and the validity of a commercial bicycle fitting system. , 1998, Applied ergonomics.

[12]  C. C. Martin,et al.  A real-time ergonomic monitoring system using the Microsoft Kinect , 2012, 2012 IEEE Systems and Information Engineering Design Symposium.

[13]  K. de Vey Mestdagh,et al.  Personal perspective: in search of an optimum cycling posture , 1998 .