Image Perception and Translation Design of Industrial Heritage Tourist Destinations Based on Big Data

HUANG Di; XU Bin; GONG Shiyao

doi:10.19554/j.cnki.1001-3563.2026.10.033

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Packaging Engineering ›› 2026, Vol. 47 ›› Issue (10) : 367-380. DOI: 10.19554/j.cnki.1001-3563.2026.10.033

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Image Perception and Translation Design of Industrial Heritage Tourist Destinations Based on Big Data

HUANG Di, XU Bin, GONG Shiyao

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Abstract

The work aims to explore the cultural tourism image characteristics and translation design paths in the renewal and development of industrial heritages, so as to promote the innovative activation of industrial heritages and the upgrading of tourism experience. With Beijing 798 Art Zone as the research case, an integrated research framework consisting of multi-modal data collection, image perception analysis, and translation innovation design was constructed. Specifically, the ResNet50 deep learning model was adopted to identify the visual features of images. Word frequency analysis, LDA topic modeling and BERT sentiment analysis were combined to explore semantic hotspots and emotional tendencies. Space syntax and POI data analysis were applied to investigate the spatial distribution and accessibility characteristics of images. Symbolic translation design was carried out for the core images. "Art" was the core perceived image of Beijing 798 Art Zone, and the scenes where core images such as graffiti and sculptures, landmark buildings, and streetscapes integrated with industrial heritage constituted the core check-in spaces of the zone. The distribution of POI hotspots was highly coupled with areas of high spatial integration, presenting an image pattern from core to edge. Based on the core image elements extracted from multi-modal data, a full-chain translation design was completed, including visual symbol extraction, stylized abstract translation and practical scenario adaptation. This research framework realizes the deep integration of image perception and translation design driven by social media data, providing practical references for the cultural inheritance, design innovation and sustainable development of industrial heritage tourist destinations.

Key words

798 Art Zone / industrial heritage / image identification / image perception / deep learning / translation design

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HUANG Di, XU Bin, GONG Shiyao. Image Perception and Translation Design of Industrial Heritage Tourist Destinations Based on Big Data[J]. Packaging Engineering. 2026, 47(10): 367-380 https://doi.org/10.19554/j.cnki.1001-3563.2026.10.033

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