The Journal of the Society for Art and Science
Online ISSN : 1347-2267
ISSN-L : 1347-2267
Papers for Expressive Japan 2018
A Self-Learning Support System for Drawing Actual Human Body Model by Pose Estimation
Hiroto NishizawaMasahiro UraKazunori Miyata
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JOURNAL FREE ACCESS

2019 Volume 18 Issue 1 Pages 19-27

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Abstract
This research proposes a learning support system for drawing on actual human body model. For beginners at drawing picture, it is not easy to grasp the human body ratio of the model and to draw a picture in accordance with the skeletal structure. The proposed system extracts posture information from an actual human body model and drawn picture, and generates skeleton line segments. Then, the system superimposes the skeleton line segments on the actual model using a transmission type display. Finally, the system gives an evaluation focused on the skeleton, using the posture data obtained by posture estimation from the drawn picture. In conclusion, we confirmed that the system improves skeletal cognitive ability and drawing skill, and is suitable for more practical drawing.
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© 2019 The Society for Art and Science
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