record

Thesis Info

LABS ID
00760
Thesis Title
Audience - Performer Engagement in Live Dance
Author
Lida Theodorou
2nd Author
3rd Author
Degree
Media and Arts Technology
Year
2018
Number of Pages
187
University
Queen Mary University of London
Thesis Supervisor
Prof. Pat Healey
Supervisor e-mail
p.healey AT qmul.ac.uk
Other Supervisor(s)
Dr. Fabrizio Smeraldi
Language(s) of Thesis
English
Department / Discipline
School of Electronic Engineering and Computer Science
Languages Familiar to Author
URL where full thesis can be found
Keywords
Audience; Engagement; Contemporary Dance; Liveness; Social Sensing
Abstract: 200-500 words
In live performances seated audiences have restricted opportunities for response, most commonly through cheering and applause at the end. However, audiences make other apparently incidental movements during a performance such as fixing hair, adjusting glasses, scratching ears, supporting their chin or shifting their bodies in the chair tochange posture. The question we address here is whether these apparently incidental movements may provide systematic clues about people’s level of engagement with a performance. Our programmatic hypothesis is that audiences’ ongoing responses are part of a bi-directional system of audience-performer communication that distinguishes live from recorded performance. What could performers be detecting in these situations that informs their dynamic sense of how well a performance is going? Existing audience research has mostly focused on the non-visible or self-reported responses, while little is known about the overt audience responses. The main aim of this research is to uncoverthese audience responses and examine whether they may provide an indication of audience engagement and thereby form part of a feedback cycle between the performers and their audience. This thesis investigates this in the hardest case of contemporary dance where the production and setting should make audience responses hard to detect. A series of live performance studies is conducted in real theatrical settings in UK. This requires the development of methods capable of capturing continuous responses of the audience and the dancers and making sense of the resulting multi-modal data. Video recordings of performers and audience are analysed using computer vision techniques to extract face and body movement data while audience hand movement is captured using specialised wearable devices. The results show that while there is no systematic relationship between the responses of audience and dancers, audience members bodymovements do signal their levels of engagement to the dancers. The empirical findings of this thesis provide evidence that stillness and blank expressions are characteristic markers of cognitive engagement during performance whereas movement and hand to facegestures typically signal restlessness or boredom. This work argues that the audience’s overt responses matter and are an important characteristic of the live experience. The audience responses that have been disclosed in this thesis can provide a systematic basisto design for audiences and suggest new forms of live experience more focused on the audience.