{
  "abstract": "Computer vision in sports increasingly supports judging, analytics, training, and injury prevention, yet Taekwondo’s high-speed kicks introduce motion blur, self-occlusion, and large joint excursions that challenge models trained on everyday actions. We release a synchronized dual-view dataset of standardized Taekwondo Poomsae (Taegeuk 1–8), recorded concurrently from frontal and lateral viewpoints in Full HD (1920 × 1080, 30 fps). Each frame includes normalized 2D coordinates and confidence scores for 12 major joints (shoulders, elbows, wrists, hips, knees, ankles), distributed as frame-aligned CSV files paired with the videos. Dual viewpoints provide complementary evidence for fast, large-amplitude lower-limb motion, enabling robust 2D pose model training/evaluation, cross-view generalization tests (e.g., train-frontal/test-lateral), and reproducible benchmarks for sports motion analysis. This resource addresses the scarcity of sports-specific, high-speed data and supports fair, replicable evaluation pipelines in computer vision.",
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  "affiliations": [
    "Department of Recreation Management; Corresponding author.",
    "Department of Computer Science & Information Engineering"
  ],
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  "arxiv": null,
  "author_total": 2,
  "authors": [
    {
      "affs": [
        0
      ],
      "name": "Chien-Chung Huang"
    },
    {
      "affs": [
        1
      ],
      "name": "Qing-Wei Zheng"
    }
  ],
  "bibtex": "https://research.draconitic.com/paper/62rm306nejxd0.bib",
  "cited_by": 0,
  "doi": "10.1016/j.dib.2026.113324",
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  "landing_url": "https://doi.org/10.1016/j.dib.2026.113324",
  "language": "en",
  "licence": "CC-BY",
  "licence_label": "CC BY",
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  "native_subjects": [
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      "lcc",
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      "lcc",
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      "1707|Human Pose and Action Recognition"
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  "pdf_url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC13718661/pdf/?tool=EBI",
  "pmcid": "PMC13718661",
  "pmid": "42959920",
  "published": "2026-08-01",
  "publisher": "Elsevier",
  "ris": "https://research.draconitic.com/paper/62rm306nejxd0.ris",
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  "subjects": [
    {
      "field": "medicine",
      "origin": "lcc:R858-859.7",
      "subfield": "general"
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  ],
  "title": "A dual-view videos and two-dimensional pose annotation dataset of Taekwondo Poomsae (Taegeuk 1–8) for human motion analysis",
  "title_text": "A dual-view videos and two-dimensional pose annotation dataset of Taekwondo Poomsae (Taegeuk 1–8) for human motion analysis",
  "type": "peer-reviewed",
  "updated_at": "2026-11-02T12:22:38Z",
  "url": "https://research.draconitic.com/paper/62rm306nejxd0",
  "venue": "Data in Brief",
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}