ART – BASED TRAINING METHODS FOR EMPOWERING ADULTS IN THE DIGITAL ERA

Since the dawn of humanity, dancing has been central to life occasions, for celebration, mourning, entertaining or even communicating. Still, it remains a vital practice around the world. With the development of technology, many efforts have been made to adapt specific choreographies and dancing rituals to the modern era, via digital platforms. However, these sequences cannot be construed as realistic when they are viewed through computers, because the actual expressions are lost in the translation. A lot of attempts have been made to provide a solution to this issue, but the most successful are the motion capturing devices and equipment. In this research, we focus on the recording of choreographies, which represent important social concepts, using a Microsoft Kinect sensor as a motion capturing device. Microsoft Kinect is chosen because it is a low-cost device that can deliver adequate results. The outcome of the research is a “handbook” in virtual reality environment, which can be used as an educational tool by anyone. The project aims at being a response to the global need of today’s world for creation of inclusive environments, where socially aware people can peacefully co – exist. The digital handbook can enhance the skills and competences of adult trainers in arts and culture and every participant gets in touch with sensitive concepts and develops social awareness. Inspiration for the project is drawn via social and humanistic values stemming from philosophical, sociological and psychological texts and it is innovative not only for its content but also for the way this is developed

Expressive movement generation with machine learning

Movement is an essential aspect of our lives. Not only do we move to interact with our physical environment, but we also express ourselves and communicate with others through our movements. In an increasingly computerized world where various technologies and devices surround us, our movements are essential parts of our interaction with and consumption of computational devices and artifacts. In this context, incorporating an understanding of our movements within the design of the technologies surrounding us can significantly improve our daily experiences. This need has given rise to the field of movement computing – developing computational models of movement that can perceive, manipulate, and generate movements. In this thesis, we contribute to the field of movement computing by building machine-learning-based solutions for automatic movement generation. In particular, we focus on using machine learning techniques and motion capture data to create controllable, generative movement models. We also contribute to the field by creating datasets, tools, and libraries that we have developed during our research. We start our research by reviewing the works on building automatic movement generation systems using machine learning techniques and motion capture data. Our review covers background topics such as high-level movement characterization, training data, features representation, machine learning models, and evaluation methods. Building on our literature review, we present WalkNet, an interactive agent walking movement controller based on neural networks. The expressivity of virtual, animated agents plays an essential role in their believability. Therefore, WalkNet integrates controlling the expressive qualities of movement with the goal-oriented behaviour of an animated virtual agent. It allows us to control the generation based on the valence and arousal levels of affect, the movement’s walking direction, and the mover’s movement signature in real-time. Following WalkNet, we look at controlling movement generation using more complex stimuli such as music represented by audio signals (i.e., non-symbolic music). Music-driven dance generation involves a highly non-linear mapping between temporally dense stimuli (i.e., the audio signal) and movements, which renders a more challenging modelling movement problem. To this end, we present GrooveNet, a real-time machine learning model for music-driven dance generation

Collaborative design in kinetic performance: safeguarding the uilleann pipes through inertial motion capture

This paper explores the possibilities of motion capture as a tool to preserve and study Intangible Cultural Heritage (ICH) practices such as playing instruments. The Uilleann pipes are both an instrument and a culture with a now strong community following and recovering after being almost extinguished several times in Ireland. The playing and making of the Uilleann pipes was incorporated into the Representative list of the UNESCO Convention of Intangible Cultural Heritage in 2017. This experience was performed in collaboration with several Uillean pipe players who contributed at every stage of the performance recording with comments and orientation. Some of these comments were also later formally kept as interviews to the players. The technical capture of the movements was done using a Rokoko Smart suit and paired Smart gloves which the piper wears for the performance. The resulting motion file was then cleaned and redirected to Blender 3D, a community made software package that allows the incorporation of a renderable avatar that helps for the dissemination of the performance. This recording process, called Inertial system, allows performers to perform almost anywhere and to capture the movements of the players with good accuracy. This process of recording and collaboration with the community is a cost-effective solution that can be of particular interest for scholars as well as for cultural communities wishing to archive these practices quickly. This design of technology and collaborative recording allows for a round experience that combined the detail of the technically enhanced recording with the interpretive nuance of the player that enriches the capturing process with mentions to how it is ‘relatively’ comfortable for the player and how efficient it is in terms of resulting detail. This collaboratively designed experience also provides the three aspects of intangible heritage preservation: supports the community -who can learn from the resulting animation; helps situating the practice within the cultural practice of the community-as they are part of the process; and helps materialise the output permitting its digital cataloguing, archival, and storage