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Football360 – Introducing a New Dataset for Camera Calibration in Sports Domain

Introduction

The aim of this dataset is to aid the development and evaluation of computer vision algorithms, primarily the radial distortion correction algorithms, in the sports domain.

This dataset contains 268 panorama images, and was created using the PANONO panoramic camera in 3 football arenas in Slovakia. Each arena was covered from numerous locations on all levels of the tribune, and broadcast camera platforms. The images capture regular football game, pitch maintenance, low/challenging lighting conditions, day and night situations.

ArenaNumber of images
Bratislava111
Trnava104
Dunajská Streda53

You can download the raw images from the following link: football360-raw.tar.gz (7.7 GB)

There is also an official GitHub repository available at: https://github.com/IgorJanos/stuFootball360

 

Raw Images

Raw images are stored as 16384×8192 JPG, they are the direct result of the PANONO stitching service.

 

Exported Sets

There are four exported datasets available for direct download and use. Each dataset contains a collection of images (data) distorted with known distortion coefficients (labels).

Set namePurposeImagesPresetDownload Link
ATraining30,000setA.jsonfootball360-setA.h5 (10.5 GB)
BTraining100,000setB.jsonfootball360-setB.h5 (35.2 GB)
CTraining300,000setC.jsonfootball360-setC.h5 (105.5 GB)
VValidation10,000setV.jsonfootball360-setV.h5 (3.5 GB)

You can see an example of how to load and use these files in a linked notebook – https://github.com/IgorJanos/stuFootball360/blob/main/notebooks/explore.ipynb

Distorted ImageCorrected Image

 

Igor Janos

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Explainable 3D convolutional neural network using GMM encoding

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Automatic Music Transcription using WaveNet

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