It is our great pleasure to welcome you to SUMAC 2021, the 3rd edition of the ACM workshop on Structuring and Understanding of Multimedia heritAge Contents. The digitization of large quantities of analogue data and the massive production of born-digital documents for many years now provide us with large volumes of varied multimedia data (images, maps, text, video, multisensor data, etc.), an important feature of which is that they are cross-domain. "Cross-domain" reflects the fact that these data may have been acquired in very different conditions: different acquisition systems, times and points of view (e.g. a 1962 postcard from the Arc de Triomphe vs. a recent street-view acquisition by mobile mapping of the same monument). These data represent an extremely rich heritage that can be exploited in a wide variety of fields, from SSH to land use and territorial policies, including smart city, urban planning, tourism, creative media and entertainment. In terms of research in computer science, they address challenging problems related to the diversity and volume of the media across time, the variety of content descriptors (potentially including the time dimension), the veracity of the data, and the 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 research topics such as multimodal and mixed media search, automatic content analysis, multimedia linking and recommendation, and big data analysis and visualization, where scientific bottlenecks may be exacerbated by the time dimension, which also provides topics of interest such as multimodal time series analysis.
The objective of this workshop is to present and discuss the latest and most significant trends in the analysis, structuring and understanding of multimedia contents dedicated to the valorization of heritage, with emphasis on the unlocking of and access to the big data of the past.
Proceeding Downloads
Deep Learning for Historical Data Analysis
This presentation will give an overview of projects on leveraging deep learning for historical data analysis my group did in the last 3 years, partly in the context of the ANR EnHerit project. I will first discuss how deep learning can be used to ...
Analyzing CHANGE in Cultural Heritage Objects through Images
Cultural heritage (CH) objects have been constantly undergoing changes/degradation over time. In order to pass the legacy of these objects to future generations, it is important to monitor, estimate and understand these changes as accurately as ...
Built Year Prediction from Buddha Face with Heterogeneous Labels
Buddha statues are a part of human culture, especially of the Asia area, and they have been alongside human civilisation for more than 2,000 years. As history goes by, due to wars, natural disasters, and other reasons, the records that show the built ...
Software and Content Design of a Browser-based Mobile 4D VR Application to Explore Historical City Architecture
The Kulturerbe4D project aims at making the diversity and change processes of architectural monuments in the urban context virtually visible and experienceable, especially for children and young people, but also for residents and tourists. A virtual ...
Evaluation of Deep Learning Techniques for Content Extraction in Spanish Colonial Notary Records
Processing and analyzing historical manuscripts is considered one of the most challenging problems in the document analysis and recognition domain. Manuscripts written in cursive are even more difficult due to overlapping words with random spacing, ...
How to Spatialize Geographical Iconographic Heritage
This article is dedicated to the spatialization of image contents, with a focus on geographical iconographic heritage, i.e. digitized or born-digital image collections, acquired at variable temporal periods and showing the territory and its human-made ...
Searching Silk Fabrics by Images Leveraging on Knowledge Graph and Domain Expert Rules
- Thomas Schleider,
- Raphael Troncy,
- Thibault Ehrhart,
- Mareike Dorozynski,
- Franz Rottensteiner,
- Jorge Sebastián Lozano,
- Georgia Lo Cicero
The production of European silk textile is an endangered intangible cultural heritage. Digital tools can nowadays be developed to help preserving it, or even to make it more accessible for the public and the fashion industry. In this paper, we propose ...
- Proceedings of the 3rd Workshop on Structuring and Understanding of Multimedia heritAge Contents
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Acceptance Rates
Year | Submitted | Accepted | Rate |
---|---|---|---|
SUMAC '22 | 6 | 5 | 83% |
Overall | 6 | 5 | 83% |