A Multiple Camera Approach to Facial Gesture Recognition for Children with Severe Spastic Quadriplegia
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Bibliographic record
Abstract
This paper presents the theoretical framework for a new approach to computer vision-based facial gesture recognition that accommodates the physiological conditions of children with severe spastic quadriplegic cerebral palsy (CP). Clinical observation suggests that these children can exploit one or more facial gestures (e.g. tongue protrusions) to operate a facial gesture access modality with adequate proficiency. The proposed approach uses independent input video data from multiple cameras observing from different viewpoints, in order to maximize the detection of intentional facial gestures in the presence of spastic head movements common to children with severe CP. Also, this paper outlines a case series methodology for further developing and evaluating the proposed algorithm and briefly discusses preliminary image processing issues.
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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