An AI Approach to Pose-based Sports Activity Classification

Title

An AI Approach to Pose-based Sports Activity Classification

Creator

Chatterjee R.; Roy S.; Islam S.K.H.; Samanta D.

Description

Artificial intelligence systems have permeated into all spheres of our life-impacting everything from our food habits to our sleep patterns. One untouched area where such intelligent systems are still in their infancy is sports. There has not been enough indulgence of AI techniques in sports, and most of the works are carried on manually by coaching staff and human appointees. We believe that intelligent systems can make coaching staff's work easier and produce findings that the human eye can often overlook. Here, we have proposed an intelligent system to analyze the beautiful game of tennis. With the use of computer vision architecture Detectron2 and activity-based pose estimation and subsequent classification, it can identify an action from a tennis shot (activity). It can produce a performance score for the player based on pose and movement like forehand and backhand. It can also be used to understand and evaluate the strengths and weaknesses of the player. The proposed approach provides a piece of valuable information for a player's performance and activity detection to be used for better coaching. The study achieves a classification accuracy of 98.60% and outperforms other SOTA CNN models. 2021 IEEE

Source

Proceedings of the 8th International Conference on Signal Processing and Integrated Networks, SPIN 2021, pp. 156-161.

Date

2021-01-01

Publisher

Institute of Electrical and Electronics Engineers Inc.

Subject

Activity; Classification; Keypoints; Pose estimation; Sports; Tennis

Coverage

Chatterjee R., School of Computer Engineering, KIIT Deemed to be University, Odisha, Bhubaneswar, 751024, India; Roy S., School of Computer Engineering, KIIT Deemed to be University, Odisha, Bhubaneswar, 751024, India; Islam S.K.H., Department of Computer Science and Engineering, Indian Institute of Information Technology Kalyani, West Bengal, Kalyani, 741235, India; Samanta D., Department of Computer Science, CHRIST Deemed to be University, Hosur Road, Karnataka, Bengaluru, 560029, India

Rights

Restricted Access

Relation

ISBN: 978-166543564-2

Format

Online

Language

English

Type

Conference paper

Identifier

https://doi.org/10.1109/SPIN52536.2021.9565996

https://www.scopus.com/inward/record.uri?eid=2-s2.0-85126263655&doi=10.1109%2fSPIN52536.2021.9565996&partnerID=40&md5=79c9be52ddde059adab0b4b0f187e2f2