A GIS-Centric Optical Tracking System and Lap Simulator for Short Track Speed Skating
Bibliographic record
Abstract
This paper presents a GIS-centric computer vision system for tracking high-speed skaters in competition and training situations. This system outputs spatio-temporal trajectories that are analyzed through presented geometric, physical and power-based models in order to evaluate sports performance. Through spatial SQL and shared database access, the GIS enables the manipulation of the trajectories and offer, amongst other, selection, fusion and completion of tracks, as well as automatic computation of distances between competitors. We propose a new method for (1) calibrating the cameras using a GIS-like image rectification method; 2) simulating trajectories and their associated power profiles to model the sport's domain; 3) incorporating the instant center of rotation in both the particle filter's dynamic model and the simulator and 4) leveraging several GIS advanced capabilities in a client-server application. Experimental results show that our rectification methology is very precise, that our tracking performance is acceptable and that the proposed power balance model is very close to the state of the art.
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How this classification was reachedexpand
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 | 0.001 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".