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A Study on Modeling Automation of Human Engineering Simulation Using Multi Kinect Depth Cameras
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 Title & Authors
A Study on Modeling Automation of Human Engineering Simulation Using Multi Kinect Depth Cameras
Jun, Chanmo; Lee, Ju Yeon; Noh, Sang Do;
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Applying human engineering simulation to analyzing work capability and movements of operators during manufacturing is highly demanded. However, difficulty in modeling digital human required for simulation makes engineers to be reluctant to utilize human simulation for their tasks. This paper addresses such problem on human engineering simulation by developing the technology to automatize human modeling with multiple Kinects at different depths. The Kinects enable us to acquire the movements of digital human which are essential data for implementing human engineering simulation. In this paper, we present a system for modeling automation of digital human. Especially, the system provides a way of generating the digital model of workers' movement and position using multiple Kinects which cannot be generated by single Kinect. Lastly, we verify the effects of the developed system in terms of modeling time and accuracy by applying the system to four different scenarios. In conclusion, the proposed system makes it possible to generate the digital human model easily and reduce costs and time for human engineering simulation.
Automation;Depth Camera;Digital Human Modeling;Ergonomics;Kinect;VRPN(Virtual Reality Peripheral Network);
 Cited by
Joung, Y.K. and Noh, S.D., Integrated Modeling and Simulation with In-line Motion Captures for Automated Ergonomic Analysis in Product Lifecycle Management, Concurrent Engineering, p.1063293X14537002, 2014. crossref(new window)

Kim, J.Y., Kim, J.I., Kim, B.K., Hong, Y.S., Kim, D.I. and Jung, G.Y., et al., 2002, Occupational Ergonomics : Work Related Musculoskeletal Disorders of the Upper Limb and Back.

Zhou, W., Armstrong, T.J., Reed, M.P., Hoffman, S.G. and Wegner, D.M., 2009, Simulating Complex Automotive Assembly Tasks Using the HUMOSIM Framework, SAE Technical Paper.

Peak, V., Vicon Motion Capture System, ed: Lake Forest, CA, 2005.

Roetenberg, D., Luinge, H. and Slycke, P., 2009, Xsens MVN: Full 6DOF Human Motion Tracking Using Miniature Inertial Sensors, Xsens Motion Technologies BV, Tech. Rep.

Jeong, Y.K. and Noh, S.D., 2012, A Study on the Automated Ergonomic Simulation using Kinect, Proceedings of the Society of CAD/CAM Engineers Conference, 2012, pp.606-610.

Lee, J.H., 2014, Advanced Human Body Tracking Method using Multiple Kinect Sensors, Thesis, Sejong University, Seoul.

Taylor II, R.M., Hudson, T.C., Seeger, A., Weber, H., Juliano, J. and Helser, A.T., 2001, VRPN: A Device-independent, Network-transparent VR Peripheral System, in Proceedings of the ACM Symposium on Virtual Reality Software and Technology, pp.55-61.

V. Team (2011, August 8). Virtual Reality Models. Available:

Moeslund, T.B. and Granum, E., 2001, A Survey of Computer Vision-based Human Motion Capture, Computer Vision and Image Understanding, 81, pp.231-268. crossref(new window)

Lu, P. and Huenerfauth, M., 2009, Accessible Motion-capture Glove Calibration Protocol for Recording Sign Language Data from Deaf Subjects, in Proceedings of the 11th International ACM SIGACCESS Conference on Computers and Accessibility, pp.83-90.

Moeslund, T.B., 2001, Interacting with a Virtual World Through Motion Capture, in Virtual Interaction: Interaction in Virtual Inhabited 3D Worlds, ed: Springer, pp.221-234.

Allard, P., Stokes, I.A. and Blanchi, J.-P., 1995, Three-dimensional Analysis of Human Movement: Human Kinetics Publishers.

Schonauer, C. and Kaufmann, H., 2011, Wide Area Motion Tracking Using Consumer Hardware, in ACM Advances in Computer Entertainment Technology Conference (ACE 2011), Lisbon, Portugal.

Martin, C.C., Burkert, D.C., Choi, K.R., Wieczorek, N.B., McGregor, P.M. and Herrmann, R., et al., 2012, A Real-time Ergonomic Monitoring System Using the Microsoft Kinect, in Systems and Information Design Symposium (SIEDS), 2012 IEEE, pp.50-55.

Suma, E., Lange, B., Rizzo, A.S., Krum, D.M., and Bolas, M., 2011, Faast: The Flexible Action and Articulated Skeleton Toolkit, in Virtual Reality Conference (VR), 2011 IEEE, pp.247-248.

Galna, B., Barry, G., Jackson, D., Mhiripiri, D., Olivier, P. and Rochester, L., 2014, Accuracy of the Microsoft Kinect Sensor for Measuring Movement in People with Parkinson's Disease, Gait Posture, 39, pp.1062-1068. crossref(new window)

Obdrzalek, S., Kurillo, G., Ofli, F., Bajcsy, R., Seto, E. and Jimison, H., et al., 2012, Accuracy and Robustness of Kinect Pose Estimation in the Context of Coaching of Elderly Population, in Engineering in Medicine and Biology Society (EMBC), 2012 Annual International Conference of the IEEE, pp.1188-1193.

Li, Q.R., Jeong, Y.K. and Noh, S.D., 2012, A Study on Modeling and Simulation of Asembly Workers' Moving Path Using Depth Camera, Proceedings of the Society of CAD/CAM Engineers Conference.