The Effect of Image Input Transformation from Inertial Measurement Unit Data on the Classification of Skateboarding Tricks

• Main Authors: Muhammad Amirul, Abdullah, Muhammad Ar Rahim, Ibrahim, Muhammad Nur Aiman, Shapiee, Muhammad Aizzat, Zakaria, Mohd Azraai, Mohd Razman, Musa, Rabiu Muazu, Anwar P. P., Abdul Majeed
• Format: Conference or Workshop Item
• Language: English
• Published: Springer 2021
• Subjects: TJ Mechanical engineering and machinery
• Online Access: http://umpir.ump.edu.my/id/eprint/32659/1/The%20effect%20of%20image%20input%20transformation%20from%20inertial%20measurement%20unit%20data%20on%20the%20classification.pdf; http://umpir.ump.edu.my/id/eprint/32659/; https://doi.org/10.1007/978-981-16-4803-8_42

This study aims to improve the classification of flat-ground tricks namely Ollie, Kickflip, Shove-it, Nollie and Frontside 180 through the identification of significant input image transformation on different transfer learning models. Six goofy skateboarders (23 years of age ± 5.0 years’ experience)...