PMID- 26812727
OWN - NLM
STAT- PubMed-not-MEDLINE
DCOM- 20180813
LR  - 20180813
IS  - 1941-0506 (Electronic)
IS  - 1077-2626 (Linking)
VI  - 23
IP  - 2
DP  - 2017 Feb
TI  - Motion Capture With Ellipsoidal Skeleton Using Multiple Depth Cameras.
PG  - 1085-1098
LID - 10.1109/TVCG.2016.2520926 [doi]
AB  - This paper introduces a novel motion capturing framework which works by 
      minimizing the fitting error between an ellipsoid based skeleton and the input 
      point cloud data captured by multiple depth cameras. The novelty of this method 
      comes from that it uses the ellipsoids equipped with the spherical harmonics 
      encoded displacement and normal functions to capture the geometry details of the 
      tracked object. This method is also integrated with a mechanism to avoid 
      collisions of bones during the motion capturing process. The method is 
      implemented parallelly with CUDA on GPU and has a fast running speed without 
      dedicated code optimization. The errors of the proposed method on the data from 
      Berkeley Multimodal Human Action Database (MHAD) are within a reasonable range 
      compared with the ground truth results. Our experiment shows that this method 
      succeeds on many challenging motions which are failed to be reported by Microsoft 
      Kinect SDK and not tested by existing works. In the comparison with the 
      state-of-art marker-less depth camera based motion tracking work our method shows 
      advantages in both robustness and input data modality.
FAU - Shuai, Liang
AU  - Shuai L
FAU - Li, Chao
AU  - Li C
FAU - Guo, Xiaohu
AU  - Guo X
FAU - Prabhakaran, Balakrishnan
AU  - Prabhakaran B
FAU - Chai, Jinxiang
AU  - Chai J
LA  - eng
PT  - Journal Article
DEP - 20160122
PL  - United States
TA  - IEEE Trans Vis Comput Graph
JT  - IEEE transactions on visualization and computer graphics
JID - 9891704
EDAT- 2016/01/27 06:00
MHDA- 2016/01/27 06:01
CRDT- 2016/01/27 06:00
PHST- 2016/01/27 06:00 [pubmed]
PHST- 2016/01/27 06:01 [medline]
PHST- 2016/01/27 06:00 [entrez]
AID - 10.1109/TVCG.2016.2520926 [doi]
PST - ppublish
SO  - IEEE Trans Vis Comput Graph. 2017 Feb;23(2):1085-1098. doi: 
      10.1109/TVCG.2016.2520926. Epub 2016 Jan 22.