Reprint

Fine Art Pattern Extraction and Recognition

Edited by
October 2021
228 pages
  • ISBN978-3-0365-2225-8 (Hardback)
  • ISBN978-3-0365-2226-5 (PDF)

This book is a reprint of the Special Issue Fine Art Pattern Extraction and Recognition that was published in

Computer Science & Mathematics
Engineering
Physical Sciences
Summary

Cultural heritage, especially the fine arts, plays an invaluable role in the cultural, historical, and economic growth of our societies. Works of fine art are primarily developed for aesthetic purposes and mainly expressed through painting, sculpture, and architecture. In recent years, owing to technological improvements and drastic cost reductions, a large-scale digitization effort has been made, which has led to the increasing availability of large, digitized fine art collections. Coupled with recent advances in pattern recognition and computer vision, this availability has provided, especially for researchers in these fields, new opportunities to assist the art community by using automatic tools to further analyze and understand works of fine arts. Among other benefits, a deeper understanding of the fine arts has the potential to make these works more accessible to a wider population, in terms of both fruition and creation, thus supporting the spread of culture.

Format
  • Hardback
License
© 2022 by the authors; CC BY-NC-ND license
Keywords
laser speckle imaging; speckle pattern; digital image correlation; nondestructive technique; artwork diagnostics; cultural heritage; portable system; cultural heritage; diagnostic images; image analysis; feature extraction; documentation; geographic information systems (GIS); image denoising; image restoration; image enhancement; stereo matching; optical flow; gradient filtering; stacked median; guided supersampling; historical photos; convolutional neural network; class activation maps; explainability; iconography; artwork analysis; color correction; chemical composition; camera characterization; Unmanned Aerial System (UAS); heritage documentation; photogrammetry; 3D modelling; eXtended Reality (XR); virtual museums; computer vision; line segmentation; line detection; line parameterization; generative adversarial networks; Fourier transform; differentiable line fitting; chain lines; paper structure; historical prints; cultural images; cultural heritage; artificial intelligence; computer vision; semantic enrichment; image analysis; digital humanities; ontologies; deep learning; image captioning; vision-language models; fine-tuning; visual art; deep learning algorithm; convolutional neural networks; pattern classification; image-based reconstruction; cultural heritage; multimodal; emotions; attention; art; modality fusion; emotion analysis; n/a