Colour-based gesture recognition for American Sign Language via Hidden Markov Models
Why this work is in the frame
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Bibliographic record
Abstract
<p>We present a new approach to gesture recognition for use in a sign<br />language learning environment. This method utilizes inexpensive<br />cloth gloves to alleviate the difficulty of hand detection and to allow<br />for feature creation. Salient colours identify the glove base and<br />fingertip markers, which are then used to extract a hand centroid<br />and a convex hull describing the fingertips for each hand. A Hidden<br />Markov Model is created for each sign, as well as an additional<br />threshold model created from all signs. When a candidate sign is<br />performed, the sign of the HMM that produces the greatest likelihood<br />is matched, provided it also exceeds the threshold model<br />likelihood. Isolated recognition testing of the training library indicated<br />76% accuracy, and continuous recognition testing showed<br />60% accuracy.</p>
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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 | 0.001 | 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