TIIS (한국인터넷정보학회)
Current Result Document :
| 한글제목(Korean Title) |
2D Human Pose Estimation based on Object Detection using RGB-D information |
| 영문제목(English Title) |
2D Human Pose Estimation based on Object Detection using RGB-D information |
| 저자(Author) |
Seohee Park
Myunggeun Ji
Junchul Chun
|
| 원문수록처(Citation) |
VOL 12 NO. 02 PP. 0800 ~ 0816 (2018. 02) |
한글내용
(Korean Abstract) |
|
영문내용
(English Abstract) |
In recent years, video surveillance research has been able to recognize various behaviors of pedestrians and analyze the overall situation of objects by combining image analysis technology and deep learning method. Human Activity Recognition (HAR), which is important issue in video surveillance research, is a field to detect abnormal behavior of pedestrians in CCTV environment. In order to recognize human behavior, it is necessary to detect the human in the image and to estimate the pose from the detected human. In this paper, we propose a novel approach for 2D Human Pose Estimation based on object detection using RGB-D information. By adding depth information to the RGB information that has some limitation in detecting object due to lack of topological information, we can improve the detecting accuracy. Subsequently, the rescaled region of the detected object is applied to ConVol.utional Pose Machines (CPM) which is a sequential prediction structure based on ConVol.utional Neural Network. We utilize CPM to generate belief maps to predict the positions of keypoint representing human body parts and to estimate human pose by detecting 14 key body points. From the experimental results, we can prove that the proposed method detects target objects robustly in occlusion. It is also possible to perform 2D human pose estimation by providing an accurately detected region as an input of the CPM. As for the future work, we will estimate the 3D human pose by mapping the 2D coordinate information on the body part onto the 3D space. Consequently, we can provide useful human behavior information in the research of HAR.
|
| 키워드(Keyword) |
RGB-D
Human Activity Recognition
Object Detection
Keypoint Localization
2D Human Pose Estimation
|
| 파일첨부 |
PDF 다운로드
|
