SUMAC '24: Proceedings of the 6th workshop on the analySis, Understanding and promotion of heritage Contents

• Tipo: Livro de Atas de Conferência Internacional
• Data: 2024

Editora

Association for Computing Machinery

New York

Conferência Internacional

MM '24: The 32nd ACM International Conference on Multimedia

Melbourne VIC Australia, 2024

Outras Informações

Abstract (EN): It is our great pleasure to welcome you to SUMAC 2024, the 6th edition of the ACM workshop on analySis, Understanding and proMotion of heritAge Contents. The workshop focuses on analyzing, processing and valorizing all types of data related to cultural heritage, including tangible and intangible heritage. As stated by UNESCO, cultural heritage provides societies with a wealth of resources inherited from the past, created in the present for the benefit of future generations. The massive digitization of historical analogue resources and production of born-digital documents provide us with large volumes of varied multimedia heritage data (images, maps, text, video, 3D objects, multi-sensor data, etc.), which represent a rich heritage that can be exploited in a wide variety of fields, from research in social sciences and computational humanities to land use and territorial policies, including urban modeling, digital simulation, archaeology, tourism, education, culture preservation, creative media and entertainment. In terms of research in computer science, artificial intelligence and digital humanities, they address challenging problems related to the diversity, specificity or volume of the media, the veracity of the data, and different user needs with respect to engaging with this rich material and the extraction of value out of the data. These challenges are reflected in the corresponding sub-fields of machine learning, signal processing, multi-modal techniques and human-machine interaction, with special focus on: Analysis of historical data, Content understanding and pattern recognition, Linking and recommendation of multi-modal digital heritage, Human-machine interaction for big data analysis and visualization, Generative modeling of cultural heritage.

Idioma: Inglês

Tipo (Avaliação Docente): Científica

ISBN: 979-8-4007-1205-0