Ice hockey shot event modeling with mixture hidden Markov model
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Bibliographic record
Abstract
In this paper we present a new event analysis framework based on mixture Hidden Markov Model(HMM) for ice hockey video. Hockey is a competitive sport, which is hard to model because of its frame color homogeneity. But it does posses many temporal regularities. With the mixture representation of local observations and Markov chain property of hockey event structure the hockey shot event is successfully modeled as a mixture HMM. Based on the mixture HMM the hockey shot event could be classified with higher accuracy. Two kinds of mixture HMM are compared for the real hockey video shot event classification. The results prove our analysis that the mixture HMM is a suitable model to deal with complex videos with intensive activities. The new mixture HMM hockey shot event model could be a very useful tool for coaches and players to analyze hockey games.
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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