International Research Journal of Innovations in Engineering and Technology - IRJIET International Open Access, Monthly, Peer Reviewed, Reputed Journal ISSN (online): 2581-3048

Impact Factor (2025): 6.9

DOI Prefix: 10.47001/IRJIET

Basketball Shots Prediction

Abstract

In current sports training, collecting and analyzing basketball player’s posture data is of great significance for enhancing the scientific of the trainer’s training plan and enhancing the athlete’s training effect. The existing basketball action recognition technology has numerous challenges similar as low effectiveness and high error rate. In order to effectively identify the basketball player’s sports posture and to make better the athlete’s training effect; this paper proposes a basketball throw gesture recognition approach to find a basis on image point birth and machine learning. First of all, the action posture data of basketball players is collected by image feature extraction approach, and multi-dimensional movement posture features are extracted from time area and frequencies area. Also, through the approach of feature selection and Gaussian secret variables, the accurate category and recognition of basketball shooting gestures are realized. The effective case analysis and the assessment of shooting action recognition effect show the superiority of the achieved basketball shooting action recognition technology. This approach can feed scientific reference and base for the development of current basketball training.

Country : India

1 Praveen Kumar B2 Mrs. Shivleela S

  1. PG Student of MCA, Dr. Ambedkar Institute of Technology, Bangalore, India
  2. Assistant Professor, Department of MCA, Dr. Ambedkar Institute of Technology, Bangalore, India

IRJIET, Volume 6, Issue 6, June 2022 pp. 179-182

doi.org/10.47001/IRJIET/2022.606022

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