시각적 복잡성 연구고찰 Ⅳ - 가로경관에서의 시각적 복잡성 모형 연구 -

Abstract

This study is related to 'Visual Complexity Research Study I, II, III'. The purpose of the study is to present the model of VC by deriving meaningful factors from six visual complexity influencing factors. The VC values were calculated from 42 photographs, and the VC levels (high-midium-low) were classified by questionnaire(209 people). Six steps analysis was performed by coding the value of VC element (6 items) and VC level (High-Medium-Low) classification frequency value for 42 pictures. First, used the one-to-one correlation of all the variables. Second, used the correlation analysis to see how the VC factors individually influence the level of VC. Based on the results of the correlation. Third, investigated the differences in analyzed distance using ANOVA. Fourth, used the multiple regression analysis to see which VC factors are relevant to the level of VC when integrated individual VC factors act in combination. Fifth, used the weighted regression analysis to see which combination of VC factors are relevant to an individual VC with no distinction in the level of VC. Sixth(using only three significant variables of analysis 5), used the weighted regression analysis again and drew a significant VC model and the weighted multiple regression equation is as follows:                            The research method used was experts survey, public questionnaire, frequency analysis, multiple regression analysis, correlation analysis, and weighted regression analysis. The value of this study is statistical evidence that sign area ratio, and vertical ratio(facade, direction 1) are the meaningful factors among VC factors. The researchers argue that the order system of visual complexity is visual physical quantity, quality of vision, and visual composition. This visual composition is the key.