Sanghyeok Oh and Yunli Lee and Kwangjin Hong and Kirak Kim and Keechul Jung
ViewPoint Insensitive Human Pose Recognition using Neural Network
2619 - 2622
2008
2
8
International Journal of Computer and Information Engineering
https://publications.waset.org/pdf/4535
https://publications.waset.org/vol/20
World Academy of Science, Engineering and Technology
This paper proposes viewpoint insensitive human
pose recognition system using neural network. Recognition system
consists of silhouette image capturing module, data driven database,
and neural network. The advantages of our system are first, it is
possible to capture multiple viewpoint silhouette images of 3D human
model automatically. This automatic capture module is helpful to
reduce time consuming task of database construction. Second, we
develop huge feature database to offer viewpoint insensitivity at pose
recognition. Third, we use neural network to recognize human pose
from multipleview because every pose from each model have similar
feature patterns, even though each model has different appearance and
viewpoint. To construct database, we need to create 3D human model
using 3D manipulate tools. Contour shape is used to convert silhouette
image to feature vector of 12 degree. This extraction task is processed
semiautomatically, which benefits in that capturing images and
converting to silhouette images from the real capturing environment is
needless. We demonstrate the effectiveness of our approach with
experiments on virtual environment.
Open Science Index 20, 2008