HCI in performance arts and the case of Illimitable Space System's multimodal interaction and visualization
Bibliographic record
Abstract
The primary aim of this art paper is to present a case study of the use of modern 3D graphics and sensor technologies in interactive stage performances. Specifically, we present studies of interactive performances in which we have used the Illimitable Space System, a proof-of-concept tool box that offers configurable multimodal interaction via a variety of means. The animation and interaction are all done in real-time and can be of arbitrary duration while the system is up and running. Earlier ISS versions were exhibited in the end of 2012 and 2013 during Open House and Stewart Hall Expo-Science events, as well during the 2014 2-day Chinese New Year Gala performance during the Ascension dance at Concordia University, Montreal, Canada, and in the large Like Shadows theatre production in Beijing, China. We describe how ISS was configured and used in these events, and the valuable feedback obtained, confidence gained in interactive technology usage in performances, and lessons learned from them. All of which help us in making continuous improvements in ISS. As a result this paper includes the themes of these events, methods, theory, and history. Since technology has been used in stage performances from ancient times, we start with a brief historical background of technology in performance arts.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.006 | 0.014 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".