Three-Dimensional Image Recognition of Athletes' Wrong Motions Based on Edge Detection
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Bibliographic record
Abstract
The traditional 3D visual motion amplitude tracking algorithms cannot acquire the complete contour features, not to mention the correction of wrong motions in sports training. To solve the problem, this paper designs a 3D visual image recognition method based on contourlet domain edge detection, and applies it to the recognition of athlete’s wrong motions in sports training. Firstly, the visual reconstruction and feature analysis of human motions were carried out, and the edge detection features were extracted by edge detection algorithm. Then, a 3D visual motion amplitude tracking method was proposed based on improved inverse kinematics. The simulation results show that the proposed algorithm can effectively realize the recognition of 3D visual images of athlete motions, and improve the correction and judgment ability of athlete motions.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it