Quantification of “complexity” in curved surface shape using total absolute curvature

•An index for quantifying complexity of curved surface shape is proposed using total absolute curvature.•The correlation between the sensory evaluation of complexity and total absolute curvature was confirmed (coefficient of determination R2 > 0.8).•The calculation method for the proposed index h...

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Veröffentlicht in:Computers & graphics 2019-02, Vol.78, p.108-115
Hauptverfasser: Matsumoto, Taishi, Sato, Koichiro, Matsuoka, Yoshiyuki, Kato, Takeo
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Sprache:eng
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Zusammenfassung:•An index for quantifying complexity of curved surface shape is proposed using total absolute curvature.•The correlation between the sensory evaluation of complexity and total absolute curvature was confirmed (coefficient of determination R2 > 0.8).•The calculation method for the proposed index has an advantages of lower calculation cost which is independent of scale, and polygon division method. [Display omitted] In recent years, with the popularization of 3D-CAD, various curved surface shapes have been used in the styling of industrial products. However, evaluation and control of shape features are done in trial and error based on the experience and intuition of the designer, causing the inefficiency of styling design. Therefore, this study aims to support the styling design by quantifying cognitive characteristics in curved surface shape. First, this research proposed total absolute curvature to quantify “complexity”, which is one of the shape features related to “beauty”, and described its geometric meaning as the total area of the Gauss map on the curved surface shape. Next, the tangible calculation method is shown by applying it to the curved surface shape represented by a triangular polygon mesh. Then, sensory evaluation experiments were carried out using three types of shapes generated by extrusion, rotation, and emergent shape generation system to confirm the applicability of the proposed quantification method. Finally, the result revealed that the logarithmic approximation between the proposed index and human perceived “complexity”.
ISSN:0097-8493
1873-7684
DOI:10.1016/j.cag.2018.10.009