Christina Volioti

The i-Treasures Intangible Cultural Heritage dataset

In this paper, we introduce the i-Treasures Intangible Cultural Heritage (ICH) dataset, a freely available collection of multimodal data captured from different forms of rare ICH. More specifically, the dataset contains video, audio, depth, motion capture data and other modalities, such as EEG or ultrasound data. It also includes (manual) annotations of data, while in some cases additional features and metadata are provided, extracted using algorithms and modules developed within the i-Treasures project. We describe the creation process (sensors, capture setups and modules used), the dataset content and the associated annotations. An attractive feature of this ICH Database is that its the first of its kind, providing annotated multimodal data for a wide range of rare ICH types. Finally, some conclusions are drawn and the future development of the dataset is discussed.

A Hybrid Content-learning Management System for Education and Access to Intangible Cultural Heritage

This paper presents an open and extendable platform that provides access to ICH resources, enables knowledge exchange between researchers and contributes to the transmission of rare know-how from their holders to the next generations. The platform is a hybrid Content-Learning Management system that permits the creation of new content of cultural heritage. It supports different user profiles for access, learning and analysis of the ICH, such as experts, learners, researchers as well as the large public. It is also supports the outcomes of sensorimotor learning functionalities of a game-based learning module. The platform integrates different modules based on multi-sensory technologies into an operating open-source content management system, which is enriched with a significant number of functionalities.

Offline statistical analysis of gestural skills in pottery interaction

The paper presents a methodology for offline statistical analysis of expert technical gestures applied in pottery interaction. The technical gestures are described using rotations of each segment of the upper-part of the body, including hands and head. The motion capture is based on a suit with inertial sensors. The results confirm the initial hypothesis that some of the body parts are highly involved in the interaction with the material (effective gestures) while others are used for obtaining specific body postures that facilitate the interaction (accompanying gestures). Principal Component Analysis has been used to confirm the hypothesis and Jackknife test to evaluate the recognition accuracy of the system using only the subset of the effective gestures. Separate databases for machine learning and testing are used to confirm that the machine is able to discriminate the technical gestures of the potter by using only information from body segments that are involved in effective gestures.

A Natural User Interface for Gestural Expression and Emotional Elicitation to Access the Musical Intangible Cultural Heritage

This article describes a prototype natural user interface, named the Intangible Musical Instrument, which aims to facilitate access to knowledge of performers that constitutes musical Intangible Cultural Heritage using off-the-shelf motion capturing that is easily accessed by the public at large. This prototype is able to capture, model, and recognize musical gestures (upper body including fingers) as well as to sonify them. The emotional status of the performer affects the sound parameters at the synthesis level. Intangible Musical Instrument is able to support both learning and performing/composing by providing to the user not only intuitive gesture control but also a unique user experience. In addition, the first evaluation of the Intangible Musical Instrument is presented, in which all the functionalities of the system are assessed. Overall, the results with respect to this evaluation were very promising.

Intangible Cultural Heritage and New Technologies: Challenges and Opportunities for Cultural Preservation and Development

Intangible cultural heritage (ICH) is a relatively recent term coined to represent living cultural expressions and practices, which are recognised by communities as distinct aspects of identity. The safeguarding of ICH has become a topic of international concern primarily through the work of United Nations Educational, Scientific and Cultural Organization (UNESCO). However, little research has been done on the role of new technologies in the preservation and transmission of intangible heritage. This chapter examines resources, projects and technologies providing access to ICH and identifies gaps and constraints. It draws on research conducted within the scope of the collaborative research project, i-Treasures. In doing so, it covers the state of the art in technologies that could be employed for access, capture and analysis of ICH in order to highlight how specific new technologies can contribute to the transmission and safeguarding of ICH.

On mapping emotional states and implicit gestures to sonification output from the 'Intangible Musical Instrument'

Sonification is an interdisciplinary field of research, aiming at generating sound from data based on systematic, objective and reproducible transformations. Towards this direction, expressive gestures play an important role in music performances facilitating the artistic perception by the audience. Moreover, emotions are linked with music, as sound has the ability to evoke emotions. In this vein, a combinatory approach which aims at gesture and emotion sonification in the context of music composition and performance is presented here. The added value of the proposed system is that both gesture and emotion are able to continuously manipulate the reproduced sound in real-time.