Alina Glushkova

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The Intangible Cultural Heritage (ICH) implies gestural knowledge and skills in performing arts, such as music, and its preservation and transmission is a worldwide challenge according to UNESCO. This paper presents an ongoing research that aims at the development of a computer vision methodology for the recognition of music-like complex hand and finger(More)
The main objective of the EU FP7 ICT i-Treasures project is to build a public and expandable platform to enable learning and transmission of rare know-how of intangible cultural heritage. A core part of this platform consists of game-like applications able to support teaching and learning processes in the ICH field. We have designed and developed four(More)
This research has been conducted in the context of the ArtiMuse project that aims at the modeling and renewal of rare gestural knowledge and skills involved in the traditional craftsmanship and more precisely in the art of wheel-throwing pottery. These knowledge and skills constitute intangible cultural heritage and refer to the fruit of diverse expertise(More)
This paper presents a unified framework computer vision approach for finger gesture early recognition and interaction that can be applied on sequences of either RGB or depth images without any supervised skeleton extraction. Either RGB or time-of-flight cameras can be used to capture finger motions. The hand detection is based on a skin color model for(More)
In this paper, we present good practices of applying and extending Random Decision Forests (RDFs) for the 3D modelling of scenes where humans interact with moving, deformable and revolving objects in a professional context. We apply our method to two use-cases; the first is in the industrial context of the luxury leather good production while the second is(More)
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