Artificial Intelligence and Digital Museum VR Environment Design Based on Embedded Image Processing

Abstract

Abstract As a carrier of human cultural heritage, it is of great practical significance to apply VR technology to the construction of modern digital museums. This paper combines artificial intelligence and SNN algorithms for image segmentation and proposes the overall framework of ‘embedded image acquisition and SNN segmentation processing’. This system is utilized to improve the picture clarity and delay efficiency of VR technology and reduce the vertigo feeling of the user experience. The VR environment of the digital museum is designed according to the user’s intentions. Finally, the effectiveness of the designed museum VR environment is verified by evaluating the comfort, interaction, and emotional experience of the VR museum. The experimental results show that in terms of comfort experience, the SSQ scale score of the VR museum experience based on the embedded image processing is 7.1, which is nearly double the score of the original VR museum experience. In terms of interaction and emotional experience, the overall satisfaction score of the VR environment design of the M museum was 9.4. The two aspects of emotional experience and cultural communication effects were evaluated as 4.27 and 4.05, respectively. It indicates that the user satisfaction of the VR environment design of the AI and digital museum based on the embedded image processing is high, and that this VR environment design can effectively improve the communication of the museum.

Cite this work

No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 2 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.