Badminton Activity Recognition (BAR)

Citation Author(s):: Indrajeet
Ghosh
University of Maryland, Baltimore County

Sreenivasan
Ramasamy Ramamurthy

University of Maryland, Baltimore County

Avijoy
Chakma
University of Maryland, Baltimore County

Emon
Dey
University of Maryland, Baltimore County

Zahid
Hasan
University of Maryland, Baltimore County

Nirmalya
Roy
University of Maryland, Baltimore County
Submitted by:: SREENIVASAN RAM...
Last updated:: Fri, 07/16/2021 - 10:03
DOI:: 10.21227/n1e0-7c60
Data Format:: tar.gz
License:: Creative Commons Attribution

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Categories:: Artificial Intelligence
Machine Learning
Signal Processing
Keywords:: CNN, K-nearest neighbor (KNN), activity recognition, Sports Analytics

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CITE

Abstract

The Badminton Activity Recognition (BAR) Dataset was collected for the sport of Badminton for 12 commonly played strokes. Besides the strokes, the objective of the dataset is to capture the associated leg movements.

Instructions:

Please refer to the README file for detailed instructions.

Comments

for testing purpose

Submitted by Shree _ on Sun, 06/20/2021 - 09:30

For Post graduate Project

Submitted by Mah Noor on Fri, 01/14/2022 - 10:25

Dataset Files

BAR-Dataset.tar.gz (1.57 GB)

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Documentation

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readme.pdf	71.07 KB

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