Saharudin Ismail
Universiti Teknologi Malaysia

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Journal : TELKOMNIKA (Telecommunication Computing Electronics and Control)

Deep learning in sport video analysis: a review Keerthana Rangasamy; Muhammad Amir As’ari; Nur Azmina Rahmad; Nurul Fathiah Ghazali; Saharudin Ismail
TELKOMNIKA (Telecommunication Computing Electronics and Control) Vol 18, No 4: August 2020
Publisher : Universitas Ahmad Dahlan

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.12928/telkomnika.v18i4.14730

Abstract

Sport is a competitive field, where it is an element of measurement for a countries development.  Due to this reason, sport analysis has become one of the major contribution in analysing and improving the performance level of an athlete.  Video-based modality has become a crucial tool used in sport analysis by coaches and performance analysis.  There were wide variety of techniques used in sport video analysis.  The main purpose of this review paper is to compare and update review between traditional handcrafted approach and deep learning approach in sport video analysis based on human activity recognition, overview of recent study in video based human activity recognition in sport analysis and finally concluded with future potential direction in sport video analysis.