Tourists’ perceptions of urban space: a computer vision approach

Abstract

Purpose This study aims to conduct an empirical investigation of differing perceptions of nine types of urban space and nine visual elements among tourists in destination using a computer vision (CV) approach. Design/methodology/approach The data for this study was extracted from YFCC 100 M dataset. Nine types of urban space in Beijing were initially identified using a scene recognition model. Subsequently, a semantic segmentation model was applied, which yielded substantial evidence relating to nine visual elements that were used to elicit differing perceptions among tourists from different continents. Findings Tourists from three continents had different perceptions about corridors, old buildings, overlooks and traffic spaces, reflecting their cultural convention. Asians, Europeans and North Americans diversely gazed at the landscape element of buildings, foliage, sky and people in urban space. All those provided evidence to contribute to the tourist gaze theory's construction. Originality/value This study firstly depicted how tourists perceive the tourism symbol of urban space. The novel approach of employing two CV models offer methodological insights to tourism research relevant to visual perception.