Cultural big data: nineteenth to twenty-first century panoramic visualization

From the nineteenth-century panorama to the emergence of the digital panoramic format in the 1990's, the visualization of large images frequently relies on panoramic viewing strategies. Originally rendered in the form of epic painted canvases, these strategies are now amplified through gigapixel imaging, computer vision and machine learning. Whether for scientific analysis, dissemination, or to visualize cultural big data, panoramic strategies pivot on the illusion of immersion. The latter is achieved through human-centered design situated within a large-scale environment combined with a multi-sensory experience spanning sight, sound, touch, and smell. In this article, we present the original research undertaken to realize a digital twin of the 1894 panorama of the battle of Murten. Following a brief history of the panorama, the methods and technological framework systems developed for Murten panorama's visualization are delineated. Novel visualization methodologies are further discussed, including how to create the illusion of immersion for the world's largest image of a single physical object and its cultural big data. We also present the visualization strategies developed for the augmentation of the layered narratives and histories embedded in the final interactive viewing experience of the Murten panorama. This article offers researchers in heritage big data new schemas for the visualization and augmentation of gigapixel images in digital panoramas.

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Publication Details

Journal
Frontiers in Big Data
Published
2024-11-08
DOI
https://doi.org/10.3389/fdata.2024.1309887
Citations
1
Primary Topic
3D Surveying and Cultural Heritage
Type
article
Field-Weighted Citation Impact
0.83

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article

Cultural big data: nineteenth to twenty-first century panoramic visualization

Daniel Jaquet, Sarah Kenderdine, Lily Hibberd, Paul Bourke et al.
1 citations
Frontiers in Big Data
3D Surveying and Cultural Heritage
0.83
article

Cultural big data: nineteenth to twenty-first century panoramic visualization

Daniel Jaquet, Sarah Kenderdine, Lily Hibberd, Paul Bourke, T. K. W. Chau
article en
1 citations

Abstract

From the nineteenth-century panorama to the emergence of the digital panoramic format in the 1990's, the visualization of large images frequently relies on panoramic viewing strategies. Originally rendered in the form of epic painted canvases, these strategies are now amplified through gigapixel imaging, computer vision and machine learning. Whether for scientific analysis, dissemination, or to visualize cultural big data, panoramic strategies pivot on the illusion of immersion. The latter is achieved through human-centered design situated within a large-scale environment combined with a multi-sensory experience spanning sight, sound, touch, and smell. In this article, we present the original research undertaken to realize a digital twin of the 1894 panorama of the battle of Murten. Following a brief history of the panorama, the methods and technological framework systems developed for Murten panorama's visualization are delineated. Novel visualization methodologies are further discussed, including how to create the illusion of immersion for the world's largest image of a single physical object and its cultural big data. We also present the visualization strategies developed for the augmentation of the layered narratives and histories embedded in the final interactive viewing experience of the Murten panorama. This article offers researchers in heritage big data new schemas for the visualization and augmentation of gigapixel images in digital panoramas.

Frontiers in Big DataVol. 7
St Vincent’s Private Hospital Sydney (AU), École Polytechnique Fédérale de Lausanne (CH)
École Polytechnique Fédérale de Lausanne, Canton de Fribourg
Sustainable cities and communities
Openalex Percentile: Top 19%
3D Surveying and Cultural Heritage
0.83
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Cultural big data: nineteenth to twenty-first century panoramic visualization — Daniel Jaquet, Sarah Kenderdine, et al. · Frontiers in Big Data (2024) | TGRS Research Map | TGRS