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Proceedings Paper • new

Discrimination of drawing collapse for animated characters by SVM
Author(s): Jun Sakurai; Tomokazu Ishikawa; Yusuke Kameda; Ichiro Matsuda; Susumu Itoh
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Paper Abstract

In general, "drawing collapse" is a word used when very low quality animated contents are broadcast. For example, perspective of the scene is unnaturally distorted and/or sizes of people and buildings are abnormally unbalanced. In our research, possibility of automatic discrimination of drawing collapse is explored for the purpose of reducing a workload for content check typically done by the animation director. In this paper, we focus only on faces of animated characters as a preliminary task, and distances as well as angles between several feature points on facial parts are used as input data. By training a support vector machine (SVM) using the input data extracted from both positive and negative example images, about 90% of discrimination accuracy is obtained when the same character is tested.

Paper Details

Date Published: 22 March 2019
PDF: 5 pages
Proc. SPIE 11049, International Workshop on Advanced Image Technology (IWAIT) 2019, 1104931 (22 March 2019); doi: 10.1117/12.2521523
Show Author Affiliations
Jun Sakurai, Tokyo Univ. of Science (Japan)
Tomokazu Ishikawa, Toyo Univ. (Japan)
Dwango CG Research (Japan)
Yusuke Kameda, Tokyo Univ. of Science (Japan)
Ichiro Matsuda, Tokyo Univ. of Science (Japan)
Susumu Itoh, Tokyo Univ. of Science (Japan)


Published in SPIE Proceedings Vol. 11049:
International Workshop on Advanced Image Technology (IWAIT) 2019
Qian Kemao; Kazuya Hayase; Phooi Yee Lau; Wen-Nung Lie; Yung-Lyul Lee; Sanun Srisuk; Lu Yu, Editor(s)

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