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pro vyhledávání: '"Teng-Chang Chen"'
Publikováno v:
The Scientific World Journal, Vol 2014 (2014)
This paper proposes a three-dimensional (3D) human posture estimation system that locates 3D significant body points based on 2D body contours extracted from two cameras without using any depth sensors. The 3D significant body points that are located
Externí odkaz:
https://doaj.org/article/4e600cb9a5964039941825c139271af6
Autor:
Teng-Chang Chen, 陳登昌
97
This thesis proposes a real-time 3D human body posture estimation method to locate different significant body points in 3D space by using 2D extracted body contours from two cameras. The located 3D significant body points include the head, ce
This thesis proposes a real-time 3D human body posture estimation method to locate different significant body points in 3D space by using 2D extracted body contours from two cameras. The located 3D significant body points include the head, ce
Externí odkaz:
http://ndltd.ncl.edu.tw/handle/45373628905614918439
Publikováno v:
IEEE Transactions on Fuzzy Systems. 19:717-728
This paper proposes the implementation of a zero-order Takagi-Sugeno-Kang (TSK)-type fuzzy neural network (FNN) on graphic processing units (GPUs) to reduce training time. The software platform that this study uses is the compute unified device archi
Publikováno v:
The Scientific World Journal, Vol 2014 (2014)
The Scientific World Journal
The Scientific World Journal
This paper proposes a three-dimensional (3D) human posture estimation system that locates 3D significant body points based on 2D body contours extracted from two cameras without using any depth sensors. The 3D significant body points that are located
Publikováno v:
2010 5th IEEE Conference on Industrial Electronics and Applications.
This paper proposes a Batch Support Vector Machine-Trained Fuzzy Classifier (BSVM-FC). The BSVM-FC is a fuzzy system that consists of Takagi-Sugeno (TS)-type fuzzy rules. For structure learning of the BSVM-FC, there are no fuzzy rules initially. The