Immersive virtual reality and computer vision for heritage: visual evaluation and perception of the industrial heritage sites along the Yunnan–Vietnam railway (Yunnan section)

Abstract

The visual composition and human perception are found to relate to the reuse and tourism of heritage railways. Previous studies have used either environmental audits and on-site interviews that have limitations in terms of cost, time, and measurement scale, or virtual perception base on two-dimension images but with gaps in interactivity, virtual immersion and field of view. This study developed an “objective + subjective” visual evaluation and perception framework integrating Computer Vision (CV) and Immersive Virtual Reality (IVR) to assess the visual quality of industrial heritage sites along the Yunnan-Vietnam Railway (Yunnan Section). The stepwise multiple linear regression models were carried out to investigate the relationship between objective evaluation and subjective perception. The results showed that 16 landscape elements of the heritage sites were successfully segmented. According to the visual perception score bands, the 120 industrial heritage sites were classified as 39 high-score sites, 66 medium-score sites, and 15 low-score sites. In general, although the sky and hard ground accounted for a higher proportion, they had little effect on the sum scores, while the vegetation, water, and buildings played a significant role in the perception of visual quality. The results can help researchers, planners, and government departments clarify the visual quality to scientifically specify bottom-up planning and management solutions for railway industrial heritage sites. Moreover, the simplicity, accuracy, and effectiveness of this framework make it suitable for large-scale visual evaluation of other railway industrial heritage sites and linear heritage sites.