☰

Nordic Skiing Video Dataset

This site provides access to a multi-view video dataset of cross-country skiing technique, along with pretrained AlphaPose model weights, annotated data, and labeled gear cycles for research use.

About

This dataset contains drone-captured video recordings of 12 skiers performing the skating technique in gears 2, 3, and 4. The skiers range from beginners to national-level athletes, providing a wide variation in technique quality and style. Several high-level skiers also performed common technical mistakes, making the dataset suitable for research on error detection.

The current version includes 149 videos, filmed from side and front perspectives. All videos were recorded at Ormberget in Luleå, northern Sweden, with a resolution of 1920×1080 pixels and a frame rate of 30 frames per second.

A subset of the videos has been annotated using the Computer Vision Annotation Tool (CVAT) in the Halpe26 format. In addition, AlphaPose model weights, raw video recordings, annotation JSON files, and labeled cycles suitable for gear classification are made available on this site.

Data Downloads (Disabled until closer to publication)

Model Weights

Raw Video Dataset

Annotated Pose Dataset

  • Annotated videos – Videos used for manually annotating pose keypoints. Download (1.23GB)
  • Keypoint pose annotations – Halpe26 keypoint annotations of annotated videos. Download (2.6MB)
  • Keypoint test videos – Short sequences used for testing model keypoint predictions. Download (28.6MB)
  • Keypoint test annotations – Manually labeled keypoints for pose model test data. Download (153kB)

Labeled Gear Cycles Dataset

  • Full labeled cycles dataset – Folder containing all labeled cycles. Download (21.2MB)
  • 90/10 Train/Test Split – Labeled cycles data randomly split into a 90% train and a 10% test set. Download (21.2MB)
  • Skier-Based Split – Labeled cycles data split into: train (all except skiers 2, 5, 10) and test (skiers 2, 5, 10 only) sets. Download (21.2MB)

GitHub

Code Repository

Go to GitHub

Publication

[Coming soon!]

Contact Us

Britta Ayano Wilde
Luleå University of Technology
Research subject:Machine Learning
Division: Embedded Intelligent Systems LAB
Department of Computer Science, Electrical and Space Engineering
Luleå
Hamam Mokayed
Associate Professor
Luleå University of Technology
Research subject:Machine Learning
Division: Embedded Intelligent Systems LAB
Department of Computer Science, Electrical and Space Engineering
+46 (0)920 492075
Luleå
Andreas Almqvist
Professor
Luleå University of Technology
Research subject: Machine Elements
Division: Machine Elements
Department of Engineering Sciences and Mathematics
+46 (0)920-492407
Luleå
Karl Löwenmark
Research Assistant
Luleå University of Technology
Research subject:Machine Learning
Division: Embedded Intelligent Systems LAB
Department of Computer Science, Electrical and Space Engineering
Luleå