iKarate: Improving Karate Kata | Zendy

Bassel Emad | Zendy; Omar Atef | Zendy; Yehya Shams | Zendy; Ahmed El-Kerdany | Zendy; Nada Shorim | Zendy; Ayman Nabil | Zendy; Ayman Atia | Zendy

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iKarate: Improving Karate Kata

Author(s) -

Bassel Emad,

Omar Atef,

Yehya Shams,

Ahmed El-Kerdany,

Nada Shorim,

Ayman Nabil,

Ayman Atia

Publication year - 2020

Publication title -

procedia computer science

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.334

H-Index - 76

ISSN - 1877-0509

DOI - 10.1016/j.procs.2020.03.090

Subject(s) - computer science , mistake , martial arts , simple (philosophy) , block (permutation group theory) , human–computer interaction , interface (matter) , artificial intelligence , operating system , mathematics , philosophy , geometry , archaeology , epistemology , bubble , maximum bubble pressure method , political science , law , history

Karate is a martial art that can be practiced using hands and feet to deliver and block strikes. Karate moves must be done in a certain way, many moves are practiced incorrectly during training. In this paper, we present a fully functional system which Karate players, coaches, judges and clubs could use. The system helps in capturing Karate moves using Kinect v2 sensor and analyzing these moves using F-DTW. Real-time feedback and a report are displayed to the users using a simple GUI (Graphical User Interface) that the users can easily use, to learn how a mistake was made, and how to fix it/learn from it. F-DTW was used for proving the concept, and an average accuracy of 90% was achieved. This Paper is mainly concerned about the moves named: Age-Uke, Mae-Geri, Gedan-Barai and Soto-Uke.

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