Kinesemiotics is the study of motivated movement informed by Linguistics, Engineering, and Computer Science. The foundation of Kinesemiotics relies on effective data collection of sensor information relating to dance performance, the development of a suitable linguistic Functional Grammar model for Dance (FGD) from which to understand dance discourse, and the development of software to analyse, store and visualise such data through that model.
The heritage of dance and ballet is carried and transmitted by both practitioners and audiences; however, for all parties we are restricted to two primary sources of data: paper based notations (Labanotation, Benesh, etc), accessible only to a restricted elite of notators; video recording, with issues with perspective, resolution, accuracy, interactivity, and lacks any link to further semantic information relating to the performance in question.
An initial collaboration with the English National Ballet showed the potential benefits and applications of sensor-based notation systems, particularly for classical ballet. Such an approach also opens up the potential for novel interaction mechanisms with the data generated, including the exploitation of virtual reality technology and considerable advancements in the modelling of a theory of movement based communication with great applicative potential.
The main objective of this project is to develop a software which interfaces with a motion capture sensor suit, coupled to a commercial grade gaming engine for data manipulation and augmentation with additional semantic data based on the FGD. The PhD will be working in research labs and will be able to access to equipment resources as appropriate.
Applicants should have, or expect to achieve, at least a 2:1 Honours degree (or equivalent) in robotics, mechatronics, biomedical engineering, or a related subject.
A relevant Master’s degree and/or experience in one or more of the following will be an advantage: computer science, human-robot interaction, linguistics or language analysis.
How to apply
All applications should be made online. Under programme name select Mechanical and Manufacturing Engineering. Please quote reference number: MZUF2018
For more information about funding your PhD, please refer to the following link; View Website