Human Body 3D Posture Estimation Using Significant Points and Two Cameras
Joint Authors
Juang, C.-F.
Chen, Teng-Chang
Du, Wei-Chin
Source
Issue
Vol. 2014, Issue 2014 (31 Dec. 2014), pp.1-17, 17 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2014-04-30
Country of Publication
Egypt
No. of Pages
17
Main Subjects
Medicine
Information Technology and Computer Science
Abstract EN
This paper proposes a three-dimensional (3D) human posture estimation system that locates 3D significant body points based on 2D body contours extracted from two cameras without using any depth sensors.
The 3D significant body points that are located by this system include the head, the center of the body, the tips of the feet, the tips of the hands, the elbows, and the knees.
First, a linear support vector machine- (SVM-) based segmentation method is proposed to distinguish the human body from the background in red, green, and blue (RGB) color space.
The SVM-based segmentation method uses not only normalized color differences but also included angle between pixels in the current frame and the background in order to reduce shadow influence.
After segmentation, 2D significant points in each of the two extracted images are located.
A significant point volume matching (SPVM) method is then proposed to reconstruct the 3D significant body point locations by using 2D posture estimation results.
Experimental results show that the proposed SVM-based segmentation method shows better performance than other gray level- and RGB-based segmentation approaches.
This paper also shows the effectiveness of the 3D posture estimation results in different postures.
American Psychological Association (APA)
Juang, C.-F.& Chen, Teng-Chang& Du, Wei-Chin. 2014. Human Body 3D Posture Estimation Using Significant Points and Two Cameras. The Scientific World Journal،Vol. 2014, no. 2014, pp.1-17.
https://search.emarefa.net/detail/BIM-1050547
Modern Language Association (MLA)
Juang, C.-F.…[et al.]. Human Body 3D Posture Estimation Using Significant Points and Two Cameras. The Scientific World Journal No. 2014 (2014), pp.1-17.
https://search.emarefa.net/detail/BIM-1050547
American Medical Association (AMA)
Juang, C.-F.& Chen, Teng-Chang& Du, Wei-Chin. Human Body 3D Posture Estimation Using Significant Points and Two Cameras. The Scientific World Journal. 2014. Vol. 2014, no. 2014, pp.1-17.
https://search.emarefa.net/detail/BIM-1050547
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1050547