• Journal of Internet Computing and Services
    ISSN 2287 - 1136(Online) / ISSN 1598 - 0170 (Print)
    http://jics.or.kr/

A Method for 3D Human Pose Estimation based on 2D Keypoint Detection using RGB-D information


Seohee Park, Myunggeun Ji, Junchul Chun, Journal of Internet Computing and Services, Vol. 19, No. 6, pp. 41-51, Dec. 2018
10.7472/jksii.2018.19.6.41, Full Text:
Keywords: video surveillance, Object Detection, Keypoint Detection, Human Pose Estimation, Deep Learning

Abstract

Recently, in the field of video surveillance, deep learning based learning method is applied to intelligent video surveillance system, and various events such as crime, fire, and abnormal phenomenon can be robustly detected. However, since occlusion occurs due to the loss of 3d information generated by projecting the 3d real-world in 2d image, it is need to consider the occlusion problem in order to accurately detect the object and to estimate the pose. Therefore, in this paper, we detect moving objects by solving the occlusion problem of object detection process by adding depth information to existing RGB information. Then, using the convolution neural network in the detected region, the positions of the 14 keypoints of the human joint region can be predicted. Finally, in order to solve the self-occlusion problem occurring in the pose estimation process, the method for 3d human pose estimation is described by extending the range of estimation to the 3d space using the predicted result of 2d keypoint and the deep neural network. In the future, the result of 2d and 3d pose estimation of this research can be used as easy data for future human behavior recognition and contribute to the development of industrial technology.


Statistics
Show / Hide Statistics

Statistics (Cumulative Counts from November 1st, 2017)
Multiple requests among the same browser session are counted as one view.
If you mouse over a chart, the values of data points will be shown.


Cite this article
[APA Style]
Seohee Park, Myunggeun Ji, & Junchul Chun (2018). A Method for 3D Human Pose Estimation based on 2D Keypoint Detection using RGB-D information. Journal of Internet Computing and Services, 19(6), 41-51. DOI: 10.7472/jksii.2018.19.6.41.

[IEEE Style]
S. Park, M. Ji and J. Chun, "A Method for 3D Human Pose Estimation based on 2D Keypoint Detection using RGB-D information," Journal of Internet Computing and Services, vol. 19, no. 6, pp. 41-51, 2018. DOI: 10.7472/jksii.2018.19.6.41.

[ACM Style]
Seohee Park, Myunggeun Ji, and Junchul Chun. 2018. A Method for 3D Human Pose Estimation based on 2D Keypoint Detection using RGB-D information. Journal of Internet Computing and Services, 19, 6, (2018), 41-51. DOI: 10.7472/jksii.2018.19.6.41.