JOURNAL BROWSE
Search
Advanced SearchSearch Tips
A Method of Pose Matching Rate Acquisition Using The Angle of Rotation of Joint
facebook(new window)  Pirnt(new window) E-mail(new window) Excel Download
 Title & Authors
A Method of Pose Matching Rate Acquisition Using The Angle of Rotation of Joint
Hyeon, Hun-Beom; Song, Su-Ho; Lee, Hyun;
  PDF(new window)
 Abstract
Recently, in rehabilitation treatment, the situation that requires a measure of the accuracy of the pose and movement of joints is being increased due to the habits and lifestyle of modern people and the environment. In particular, there is a need for active automated system that can determine itself for the matching rate of pose Basically, a method for measuring the matching rate of pose is used by extracting an image using the Kinect or extracting a silhouette using the imaging device. However, in the case of extracting a silhouette, it is difficult to set the comparison, and in the case of using the Kinect sensor, there is a disadvantages that high accumulated error rate according to movement. Therefore, In this paper, we propose a method to reduce the accumulated error of matching rate of pose getting the rotation angle of joint by measuring the real-time amount of change of 9-axis sensor. In particular, it can be measured same conditions that unrelated of the physical condition and unaffected by the data for the back and forth movement, because of it compares the current rotation angle of the joint. Finally, we show a comparative advantage results by compared with traditional method of extracting a silhouette and a method using a Kinect sensor.
 Keywords
Pose;Matching rate;Angle of rotation;Angle of joint;
 Language
Korean
 Cited by
 References
1.
C. Tuzun, I. Yorulmaz, A. Cindas, S. Vatan "Low Back Pain and Posture," Clinical Rheumatology, Vol. 18, No. 4, pp. 308-312, 1999. crossref(new window)

2.
B.W Lee, H.S Shin, "Feasibility Study of Sitting Posture Monitoring Based on Piezoresistive Conductive Film-Based Flexible Force Sensor," Sensors Journal, IEEE, Vol. 16, No. 1, pp. 15-16, 2015. crossref(new window)

3.
C.J. Kucik M.D, M.A, D.M.C.C, F.C.C.P, "Telemedicine and Future Innovations," Trauma Team Dynamics, pp. 187-192, 2016.

4.
J.R. Andrews, G.L. Harrelson, K.E. Wilk, "Physical Rehabilitation of the Injured Athlete," pp. 1-618, 2012.

5.
S.Y Kwok, H.R Byun, "People Detection, Tracking and Silhouette Extraction System for Humanoid Robots," Institute of Korea Communication Sciences, Vol. 34, No. 6, pp. 593-603, 2009 (in Korean).

6.
L. Herda, P. Fua, R. Plankers, R. Boulic, D. Thalmann, "Using Skeleton-based Tracking to Increase The Reliability of Optical Motion Capture," ELSEVIER Human Movement Science, Vol. 20, No. 3, pp. 313-341, 2001. crossref(new window)

7.
L.A. Schwarz, A. Mkhitaryan, D. Mateus, N. Navab, "Human Skeleton Tracking from Depth Data Using Geodesic Distances and Optical Flow," ELSEVIER Image and Vision Computing, Vol. 30, No. 3, pp. 217-226, 2012. crossref(new window)

8.
U.Y. Usta, "Comparison of Quaternion and Euler Angle Methods for Joint Angle Animation of Human Figure Models," Storming Media, 1999.

9.
Books Llc, "Gyroscopes: Gyrocompass, Gyroscope, Inertia, Reaction Wheel, Gimbal Lock, Control Moment Gyroscope, Vibrating Structure Gyroscope," General Books LLC, 2010.