Investigating group behavior in dance: an evolutionary dynamics approach

Özcimder, Kayhan; Dey, Biswadip; Lazier, Rebecca J.; Trueman, Daniel; Leonard, Naomi Ehrich

doi:10.1109/acc.2016.7526687

Cited by 12 publications

(7 citation statements)

References 15 publications

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“…Indeed, after careful consideration of the body the task of creating a robot which compares in expressivity begins to seem nearly impossible. Analytical models, which acknowledge the nonlinearity 4 of something as complex as improvisation, have been used to try and describe this behavior inside structured improvisations in performance as in [37] or to generate diverse movement through chaotic models [38]. Our goal in this article is to extract 4 We could offer an entire discussion around the use of this word.…”

Section: Improvisational Technologymentioning

confidence: 99%

Choreographic and Somatic Approaches for the Development of Expressive Robotic Systems

LaViers

Cuan²,

Heimerdinger

et al. 2018

Arts

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As robotic systems are moved out of factory work cells into human-facing environments questions of choreography become central to their design, placement, and application. With a human viewer or counterpart present, a system will automatically be interpreted within context, style of movement, and form factor by human beings as animate elements of their environment. The interpretation by this human counterpart is critical to the success of the system's integration: "knobs" on the system need to make sense to a human counterpart; an artificial agent should have a way of notifying a human counterpart of a change in system state, possibly through motion profiles; and the motion of a human counterpart may have important contextual clues for task completion. Thus, professional choreographers, dance practitioners, and movement analysts are critical to research in robotics. They have design methods for movement that align with human audience perception; they can help identify simplified features of movement that will effectively accomplish human-robot interaction goals; and they have detailed knowledge of the capacity of human movement. This article provides approaches employed by one research lab, specific impacts on technical and artistic projects within, and principles that may guide future such work. The background section reports on choreography, somatic perspectives, improvisation, the Laban/Bartenieff Movement System, and robotics. From this context methods including embodied exercises, writing prompts, and community building activities have been developed to facilitate interdisciplinary research. The results of this work are presented as an overview of a smattering of projects in areas like high-level motion planning, software development for rapid prototyping of movement, artistic output, and user studies that help understand how people interpret movement. Finally, guiding principles for other groups to adopt are posited.

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Section: Improvisational Technologymentioning

confidence: 99%

Choreographic and Somatic Approaches for the Development of Expressive Robotic Systems

LaViers

Cuan²,

Heimerdinger

et al. 2018

Arts

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“…However, the research is limited to single instances of a dancer, thus not taking into account the simultaneous act of dancing. The interaction between performers themselves has been studied in the psychological domain [30,46]. The interaction between the public and the performers has also been investigated by [45].…”

Section: Related Workmentioning

confidence: 99%

Salsa dance learning evaluation and motion analysis in gamified virtual reality environment

Senecal

Nijdam

Aristidou

et al. 2020

Multimed Tools Appl

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Learning couple dance such as salsa is challenging as it requires to understand and assimilate all the dance skills (guidance, rhythm, style) correctly. Salsa is traditionally learned by attending a dancing class with a teacher and practice with a partner, the difficulty to access such classes though, and the variability of dance environment can impact the learning process. Understanding how people learn using a virtual reality platform could bring interesting knowledge in motion analysis and can be the first step toward a complementary learning system at home. In this paper, we propose an interactive learning application in the form of a virtual reality game, that aims to help the user to improve its salsa dancing skills. The application was designed upon previous literature and expert discussion and has different components that simulate salsa dance: A virtual partner with interactive control to dance with, visual and haptic feedback, and a game mechanic with dance tasks. This application is tested on a two-class panel of 20 regular and 20 non-dancers, and their learning is evaluated and analyzed through the extraction of Musical Motion Features and the Laban Motion Analysis system. Both motion analysis frameworks were compared prior and after training and show a convergence of the profile of non-dancer toward the profile of regular dancers, which validates the learning process. The work presented here has profound implications for future studies of motion analysis, couple dance learning, and human-human interaction.

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“…However, the research is limited to single instances of a dancer, thus not taking into account the simultaneous act of dancing. The interaction between performers themselves has been studied in the psychological domain (Ozcimder et al, 2016;Whyatt and Torres, 2017), even with the audience, that take part in the performing process (Theodorou et al, 2016).…”

Section: State Of the Artmentioning

confidence: 99%

Classification of Salsa Dance Level using Music and Interaction based Motion Features

Senecal

Nijdam

Thalmann

2019

Proceedings of the 14th International Joint Conference on Computer Vision, Imaging and Computer Graphics Theory and Application

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Learning couple dance such as Salsa is a challenge for the modern human as it requires to assimilate and understand correctly all the dance parameters. Traditionally learned with a teacher, some situation and the variability of dance class environment can impact the learning process. Having a better understanding of what is a good salsa dancer from motion analysis perspective would bring interesting knowledge and can complement better learning. In this paper, we propose a set of music and interaction based motion features to classify salsa dancer couple performance in three learning states (beginner, intermediate and expert). These motion features are an interpretation of components given via interviews from teacher and professionals and other dance features found in systematic review of papers. For the presented study, a motion capture database (SALSA) has been recorded of 26 different couples with three skill levels dancing on 10 different tempos (260 clips). Each recorded clips contains a basic steps sequence and an extended improvisation sequence during two minutes in total at 120 frame per second. Each of the 27 motion features have been computed on a sliding window that corresponds to the 8 beats reference for dance. Different multiclass classifier has been tested, mainly k-nearest neighbours, Random forest and Support Vector Machine, with an accuracy result of classification up to 81% for three levels and 92% for two levels. A later feature analysis validates 23 out of 27 proposed features. The work presented here has profound implications for future studies of motion analysis, couple dance learning and human-human interaction.

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Investigating group behavior in dance: an evolutionary dynamics approach

Cited by 12 publications

References 15 publications

Choreographic and Somatic Approaches for the Development of Expressive Robotic Systems

Choreographic and Somatic Approaches for the Development of Expressive Robotic Systems

Salsa dance learning evaluation and motion analysis in gamified virtual reality environment

Classification of Salsa Dance Level using Music and Interaction based Motion Features

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