Data · dataset · 2026
Kinematic-Pass: An Open-Source HSV-Based Ball Tracking and Trajectory Mapping System for Skill Assessment
Listed in Teesside University Research Data Repository
Description
Abstract
This dataset encompasses the cross-platform source code, algorithmic tracking logic, and interface architecture for an automated computer vision framework engineered to evaluate motor skills and frequency metrics in table tennis through the standardized wall-pass test. Developed using a decoupled dual-stack layout—utilizing a high-performance Python back-end powered by OpenCV and a responsive web-based HTML5/JavaScript dashboard—this system automates the diagnostic evaluation of athletic coordinates without laboratory-bound sensors.
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The computational core leverages real-time color segmentation within the Hue-Saturation-Value (HSV) color space combined with morphological noise filtration (erosion/dilation) to isolate ball dynamics based on high-circularity contour parameters. Concurrently, a localized pixel threshold matrix defines the dynamic "wall target zone." The tracking engine utilizes a bounded deque memory buffer to reconstruct fading 2D spatial trajectories while applying mathematical cross-over logic to count successful passes as the ball centroid bisects the calibrated target quadrants.
This data package includes complete backend multi-color tracking configurations, configuration scripts, and styling templates, offering a foundational toolkit for sports scientists, performance analysts, and table tennis coaches looking to digitize reactive training paradigms. Keywords: Computer Vision in Sports, HSV Color Segmentation, Object Tracking, Table Tennis Analytics, Wall Pass Test
Links
Where it is published
- DOI doi.org/10.17632/7hrv5rvnjn.1 ↗
DOI / persistent id · from researchdata tees ac uk
Catalogue records · 1
- OAI-PMH record data.mendeley.com/oai?verb=GetRecord&metadataPrefix=oai_dc&identifier=oai%3Adata… ↗
metadata API · from researchdata tees ac uk
Topics
- From keywords
- Computer Science & AI · Earth & Environmental Science · Engineering · Humanities · Life Sciences · Social Science
- Inferred from text
- Computer vision and multimedia computation 74% · Tabular 65%
Provenance · 1 source records, 13 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| Teesside University Research Data Repository | oai:data.mendeley.com/7hrv5rvnjn.1 | 11 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| access_level | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].anzsrc:group:4603 | enrichment · researchdata tees ac uk | taxonomy-embedding@1.0.0 | title+keywords+description (74%) |
| concepts[field].local:field:computer-science-ai | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:earth-environmental | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:engineering | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:humanities | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:life-sciences | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[field].local:field:social-science | mapping · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| concepts[modality].local:modality:tabular | enrichment · researchdata tees ac uk | keyword-concept-rules@1.0.0 | title+description (65%) |
| description | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/description |
| license | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/rights |
| publication_date | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | |
| title | source · researchdata tees ac uk | connector:researchdata_tees_ac_uk@1.0.0 | /metadata/dc/title |