International Workshop on Fine Art Pattern Extraction and Recognition
Форма участия: Очная
Срок подачи заявок: 15.06.2020
Индексирование сборника: Springer
The cultural heritage, in particular fine art, has invaluable importance for the cultural, historic and economic growth of our societies. Fine art is developed primarily for aesthetic purposes and it is mainly concerned with paintings, sculptures and architectures. In the last years, due to technology improvements and drastically declining costs, a large scale digitization effort has been made, leading to a growing availability of large digitized fine art collections. This availability, along with the recent advancements in Pattern Recognition and Computer Vision, has opened new opportunities to computer science researchers to assist the art community with automatic tools to analyze and further understand fine arts. Among the others, a deeper understanding of fine arts has the potential to make them more accessible to a wider population, both in terms of fruition and creation, thus supporting the spread of culture.
The ability to recognize meaningful patterns in fine art inherently falls within the domain of human perception and this perception can be extremely hard to conceptualize. Thus, visual-related features, such as those automatically learned by deep learning models, can be the key to tackle to problem of extracting useful representations from low-level colour and texture features. These representations can assist various art-related tasks, ranging from object detection in paintings to artistic style categorization, useful for example in museum and art gallery Websites.
The aim of the workshop is to provide an international forum for those who wish to present advancements in the state-of-the-art, innovative research, ongoing projects, academic and industrial reports on the application of visual pattern extraction and recognition for a better understanding and fruition of fine arts. The workshop solicits contribution from diverse areas such as Pattern Recognition, Computer Vision, Artificial Intelligence and Image Processing.
Topics
Topics of interest include, but are not limited to:
- Application of machine learning and deep learning to cultural heritage
- Computer vision and multimedia data
- Generative adversarial networks for artistic data
- Augmented and virtual reality for cultural heritage
- 3D reconstruction of historical artifacts
- Historical document analysis
- Content-based retrieval in the art domain
- Speech, audio and music analysis from historical archives
- Digitally enriched museum visits
- Smart interactive experiences in cultural sites
- Projects, products or prototypes for cultural heritage restoration, preservation and fruition