Name
Abstract | ||
|---|---|---|
Real time human body motion estimation plays an important role in the perception for robotics nowadays, especially for the applications of human robot interaction and service robotics. In this paper, we propose a method for real-time 3D human body motion estimation based on 3-layer laser scans. All the useful scanned points, presenting the human body contour information, are subtracted from the learned background of the environment. For human contour feature extraction, in order to avoid the situations of unsuccessful segmentation, we propose a novel iterative template matching algorithm for clustering, where the templates of torso and hip sections are modeled with different radii. Robust distinct human motion features are extracted using maximum likelihood estimation and nearest neighbor clustering method. Subsequently, the positions of human joints in 3D space are retrieved by associating the extracted features with a pre-defined articulated model of human body. Finally we demonstrate our proposed methods through experiments, which show accurate human body motion tracking in real time. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1109/URAI.2011.6145980 | URAI |
Keywords | Field | DocType |
torso templates,human contour feature extraction,pattern clustering,robotic perception,image matching,human robot interaction,iterative template matching for clustering,human-robot interaction,maximum likelihood estimation,optical scanners,service robots,iterative template matching algorithm,motion estimation,human body motion estimation,multilayer laser scans,feature extraction,object tracking,service robotics,human body motion tracking,real time 3d human body motion estimation,nearest neighbor clustering method,multi-layer laser scans,hip templates,3-layer laser scans,human body contour information,robot vision,motion tracking,nearest neighbor,maximum likelihood estimate,real time,template matching,laser scanning,human body | Template matching,Computer vision,Pattern recognition,Segmentation,Computer science,Feature extraction,Video tracking,Artificial intelligence,Motion estimation,Cluster analysis,Robotics,Match moving | Conference |
ISBN | Citations | PageRank |
978-1-4577-0722-3 | 2 | 0.38 |
References | Authors | |
8 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Wei Wang | 1 | 1679 | 168.84 |
| Drazen Brscic | 2 | 148 | 10.38 |
| Zhiwei He | 3 | 20 | 6.27 |
| Sandra Hirche | 4 | 961 | 106.36 |
| Kolja Kühnlenz | 5 | 430 | 40.87 |