Discrimination of drawing collapse for animated characters by SVM

Jun Sakurai; Tomokazu Ishikawa; Yusuke Kameda; Ichiro Matsuda; Susumu Itoh

doi:10.1117/12.2521523

22 March 2019 Discrimination of drawing collapse for animated characters by SVM

Jun Sakurai, Tomokazu Ishikawa, Yusuke Kameda, Ichiro Matsuda, Susumu Itoh

Proceedings Volume 11049, International Workshop on Advanced Image Technology (IWAIT) 2019; 1104931 (2019) https://doi.org/10.1117/12.2521523
Event: 2019 Joint International Workshop on Advanced Image Technology (IWAIT) and International Forum on Medical Imaging in Asia (IFMIA), 2019, Singapore, Singapore

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.

Citation Download Citation

Jun Sakurai, Tomokazu Ishikawa, Yusuke Kameda, Ichiro Matsuda, and Susumu Itoh "Discrimination of drawing collapse for animated characters by SVM", Proc. SPIE 11049, International Workshop on Advanced Image Technology (IWAIT) 2019, 1104931 (22 March 2019); https://doi.org/10.1117/12.2521523

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