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An Implementation of Taekwondo Action Recognition System using Multiple Sensing
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 Title & Authors
An Implementation of Taekwondo Action Recognition System using Multiple Sensing
Lee, Byong Kwon;
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 Abstract
There are a lot of sports when you left the victory and the defeat of the match the referee subjective judgment. In particular, TaeKwonDo pumse How accurate a given action? Is important. Objectively evaluate the subjective opinion of victory and defeat in a sporting event and the technology to keep as evidence is required. This study was implemented a system for recognizing Taekwondo executed through the number of motion recognition device. Step Sensor also used to detect a user`s location. This study evaluated the rate matching the standard gesture data and the motion data. Through multiple gesture recognition equipment was more accurate assessment of the Taekwondo action.
 Keywords
Gesture Recognition;Motion Capture;Correlation Analysis;Multiple Camera Recognition;Teakwondo Evaluation;
 Language
Korean
 Cited by
 References
1.
S. Ghosh, A. Konar, and A.K. Nagar, "Gesture Recognition from Indian Classical Dance Using Kinect Sensor," Proceeding of IEEE Fifth International Conference on Computational Intelligence, Communication Systems and Networks, pp. 3-8, 2013.

2.
K. Lai, J. Konrad, and P. Ishwar, "A Gesture-driven Computer Interface Using Kinect," Proceeding of IEEE Southwest Symposium on Image Analysis and Interpretation, pp. 22-24, 2012.

3.
K.K. Biswas and S.K. Basu, "Gesture Recognition Using Microsoft Kinect," Proceedings of the 5th International Conference on Automation, Robotics and Applications Dec 6-8, pp 100-103. 2011.

4.
T. Gill, J.M. Keller, D.T. Anderson, and R.H. Luke III, "A System for Change Detection and Human Recognition in Voxel Space Using the Microsoft Kinect Sensor," Proceeding of IEEE Applied Imagery Pattern Recognition Workshop, pp. 11-13, 2011.

5.
A. Shingade1 and A. Ghotkar2, “Animation of 3D Human Model Using Markerless Motion Capture Applied To Sports,” International Journal of Computer Graphics & Animation, Vol. 4, No. 1, pp. 21, 2014. crossref(new window)

6.
C. Yunyeon, T.Jiamei, J. Seungeun, K. Sangwook, “User Customizable Hit Action Recognition Method using Kinect,” Journal of Korea Multimedia Society Vol. 18, No. 4, April pp. 557-564, 2015. crossref(new window)

7.
D. Lee and Y. Nakamura, "Motion Capturing from Monocular Vision by Statistical Inference Based on Motion Database: Vector Field Approach," Proceeding of IEEE/RSJ International Conference on Intelligent Robots and Systems, pp. 617-623, 2007.

8.
M. Gabel, R. Gilad-Bachrach, and E. Renshaw, "Full Body Gait Analysis with Kinect," Engineering in Medicine and Biology Society, pp. 1964 -1967, 2012.

9.
S. Izadi, D. Kim, O. Hilliges, D. Molyneaux, R. Newcombe, P. Kohli, J. Shotton, et al., "Kinectfusion: Realtime 3D Reconstruction and Interaction Using a Moving Depth Camera," Proceedings of the 24th Annual ACM Symposium on User Interface Software and Technology, pp. 559-568, 2011.

10.
H. Jungong, L. Shao, D. Xu, and J. Shotton, “Enhanced Computer Vision with Microsoft Kinect Sensor: A Review,” IEEE Transactions on Cybernetics, Vol. 43, No. 5, pp 1318-1334. 2013. crossref(new window)