Pregled bibliografske jedinice broj: 837770
Real-Time Human Body Motion Estimation Based on Multi- Layer Laser Scans
Real-Time Human Body Motion Estimation Based on Multi- Layer Laser Scans // The 8th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI 2011)
Incheon, 2011. str. 297-302 doi:10.1109/URAI.2011.6145980 (predavanje, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
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Naslov
Real-Time Human Body Motion Estimation Based on Multi- Layer Laser Scans
Autori
Wang, Wei ; Brščić, Dražen ; He, Zhiwei ; Hirche, Sandra ; Kühnlenz, Kolja
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
The 8th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI 2011)
/ - Incheon, 2011, 297-302
Skup
The 8th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI 2011)
Mjesto i datum
Incheon, Republika Koreja, 23.11.2011. - 26.11.2011
Vrsta sudjelovanja
Predavanje
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
human body motion estimation ; multi-layer laser scans ; iterative template matching for clustering
Sažetak
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 estima- tion 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 envi- ronment. For human contour feature extraction, in or- der to avoid the situations of unsuccessful segmentation, we propose a novel iterative template matching algorithm for clustering, where the templates of torso and hip sec- tions are modeled with different radii. Robust distinct hu- man motion features are extracted using maximum likeli- hood 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.
Izvorni jezik
Engleski
Znanstvena područja
Računarstvo, Temeljne tehničke znanosti