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.

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

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)