Artificial neural networks for real-time optical hand posture recognition using a color-coded glove
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Bibliographic record
Abstract
Optical pose recognition of the hand is an extremely attractive method for user-computer interaction in many applications. The image of a hand in the frame of a video camera is processed and the pose it is making, its current finger configuration, is detected. Often combined with position tracking, it allows for a very natural way of giving commands. Furthermore, it alleviates the use of sometimes cumbersome pieces of hardware. Within immersive virtual reality systems, the liberty of movement of the commanding hand requires extra considerations not normally dealt with by typical optical hand posture recognition interfaces for desktop system applications. This research proposes an artificial neural network approach to the recognition of hand postures. The optical capture inside an immersive virtual reality workspace and the extraction of features of this hand are facilitated by the use of a specially coded color glove.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it