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

Area of Science:

• Digital Heritage
• Computer Vision
• Human-Computer Interaction

Background:

• Panoramic viewing strategies have evolved from 19th-century painted canvases to 1990s digital formats, amplified by gigapixel imaging, computer vision, and machine learning.
• These strategies are crucial for scientific analysis, dissemination, and visualizing cultural big data, primarily by creating an illusion of immersion.
• Immersion is achieved through human-centered design in large-scale environments and multi-sensory experiences (sight, sound, touch, smell).

Purpose of the Study:

• To present original research on creating a digital twin of the 1894 Murten panorama.
• To delineate the methods and technological framework for visualizing the Murten panorama.
• To discuss novel visualization methodologies for enhancing immersion and augmenting layered narratives in cultural big data.

Main Methods:

• Historical research on the Murten panorama.
• Development of a technological framework for gigapixel image visualization.
• Implementation of human-centered design and multi-sensory elements for an immersive experience.
• Application of computer vision and machine learning techniques.

Main Results:

• Successful creation of a digital twin for the 1894 Murten panorama.
• Development of novel visualization methodologies for the world's largest image of a single physical object.
• Augmentation of layered narratives and histories within an interactive viewing experience.
• Demonstration of enhanced immersion through a multi-sensory approach.

Conclusions:

• The digital twin of the Murten panorama offers a new model for visualizing and augmenting cultural heritage big data.
• Novel visualization strategies enhance the illusion of immersion for gigapixel images in digital panoramas.
• This research provides valuable schemas for researchers working with heritage big data and digital panoramas.