Visual order of Chinese ink paintings

Visual Computing for Industry, Biomedicine, and Art

Table 1 Linear regression model predicting the paintings’ visual order

Model Summary
R² = 0.627 adj. R² = 0. 609 F = 34.694 Sig. = 0.00
Variable	Regression coefficients	Standard error	Significance
White space	0.234	0.056	0.000
Mass Center’s Distance to Center	0.163	0.054	0.004
SYM-G	−0.311	0.059	0.000
Constant	4.996	0.051	0.000

R² R-Squared, adj. R² adjusted R-Squared, F F-statistic, Sig. model significance