TY - GEN
T1 - Computer facial animation with synthesize marker on 3D faces surface
AU - Gunanto, Samuel Gandang
AU - Hariadi, Mochamad
AU - Yuniarno, Eko Mulyanto
N1 - Publisher Copyright:
© 2016 IEEE.
PY - 2017/4/24
Y1 - 2017/4/24
N2 - An animated character has its own characteristics and behaviour. The animator needs to be skilled enough to make a complex animation, especially on making face expression. a Well defined facial expression can represent the emotional condition and make the animation more expressing the mood. But most facial animation is done by manually, frame-by-frame. It is very time-consuming. This research proposed a combination methods for handling the facial animation based on marker location and face surface from the 3D character. The motion data captured based on the location and movement of the marker then implemented on 3D face model to generate the motion guidance. As a guidance, this marker data role as a centroid of a vertex cluster. The cluster provided by implementing segmentation fp-NN Clustering method based on surface and can visualize the deformation using linear blend skinning methods. The result from this research shows that this system can automatically generate facial animations based on the marker data and the surface segmentation. The visualization of deformation arranges accordingly to the motion captured data and organized sequentially.
AB - An animated character has its own characteristics and behaviour. The animator needs to be skilled enough to make a complex animation, especially on making face expression. a Well defined facial expression can represent the emotional condition and make the animation more expressing the mood. But most facial animation is done by manually, frame-by-frame. It is very time-consuming. This research proposed a combination methods for handling the facial animation based on marker location and face surface from the 3D character. The motion data captured based on the location and movement of the marker then implemented on 3D face model to generate the motion guidance. As a guidance, this marker data role as a centroid of a vertex cluster. The cluster provided by implementing segmentation fp-NN Clustering method based on surface and can visualize the deformation using linear blend skinning methods. The result from this research shows that this system can automatically generate facial animations based on the marker data and the surface segmentation. The visualization of deformation arranges accordingly to the motion captured data and organized sequentially.
KW - facial animation
KW - feature marker
KW - surface
UR - http://www.scopus.com/inward/record.url?scp=85019437969&partnerID=8YFLogxK
U2 - 10.1109/ICIMECE.2016.7910452
DO - 10.1109/ICIMECE.2016.7910452
M3 - Conference contribution
AN - SCOPUS:85019437969
T3 - 2016 2nd International Conference of Industrial, Mechanical, Electrical, and Chemical Engineering, ICIMECE 2016
SP - 260
EP - 263
BT - 2016 2nd International Conference of Industrial, Mechanical, Electrical, and Chemical Engineering, ICIMECE 2016
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2nd International Conference of Industrial, Mechanical, Electrical, and Chemical Engineering, ICIMECE 2016
Y2 - 6 October 2016 through 7 October 2016
ER -