VALIDATION OF A VISUAL PERCEPTION MODEL

Validation of a perception model is presented. Based on a newly developed mathematical perception theory the visual perception is modelled as a probabilistic process obtaining and interpreting visual data from the environment. A perception derivative, namely visual openness perception, is investigated. The openness perception is quantified by means of a mapping function which converts distance data to perception information. In an experiment 30 human experimenters provided 180 openness perception statements. From this data a representative set of statements is derived by means of clustering, where the statistical properties of the data set are duly taken into account. From this representative set the openness perception model is optimized by means of a genetic algorithm. This way minimal difference between modelled perception and the perception statements is achieved. The outcome of this work is a validated openness perception model, which is representative for the perception of the experimenters in the spatial environment considered. It can be applied to measure the visual openness of spaces during architectural design, which can be essential information provision guiding the design. It is also applicable in the analysis of existing architecture to determine its openness perception properties.