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Printed Patterns for Enhanced Shape Perception of Papercraft Models
Author(s) -
Xue Su,
Chen Xuejin,
Dorsey Julie,
Rushmeier Holly
Publication year - 2010
Publication title -
computer graphics forum
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.578
H-Index - 120
eISSN - 1467-8659
pISSN - 0167-7055
DOI - 10.1111/j.1467-8659.2009.01632.x
Subject(s) - computer science , perception , limiting , 3d printed , geometric shape , artificial intelligence , geometric pattern , geometric design , geometric modeling , computer vision , computer graphics (images) , mathematics , geometry , engineering , mechanical engineering , neuroscience , biomedical engineering , biology
Papercraft models can serve as inexpensive prototypes in shape design applications. However, in making the models some geometric detail is necessarily lost, and artificial creases may be visible, thereby limiting the utility of these models. To compensate for these practical limitations, we introduce the use of printed patterns on papercraft models to enhance the perception of the shape they are intended to represent. We propose pattern generation schemes that modulate the sizes, directions, and densities of glyphs of patterns based on geometric attributes. We present a psychophysical experiment designed to explore the effect that printed patterns have on the perception of the papercraft model shapes. We find that models with printed patterns are perceived to represent the intended shape more accurately, and, further, that the type of printed pattern has an impact on the perceived shape.