Point Guard -- Computer Vision-Based Interactive Basketball Training
Platform.
Abstract
The scope and precision of basketball skill development
are sometimes restricted using subjective evaluation and manual
observation in traditional training methods. The goal of this research
is to develop a complete platform that combines data analytics, machine
learning, and computer vision to precisely deliver feedback on players’
movements, shooting mechanics, strength training regimens, and player
progress. The Computer Vision-Based Interactive Basketball Training
Platform - Point Guard will use the existing literature on sports
technology and methods of basketball training to present a game-changing
solution for basketball training. The body will be tracked by computer
vision algorithms to get quantitative feedback on a player’s agility,
footwork, and body alignment to refine all training paradigms. Hoop
Tracking allows players to practice their shooting skills while their
shot mechanics and trajectory are analyzed with state-of-the-art
computer vision techniques. Strength Training is a set of individual
exercise programs designed based on user feedback that emphasizes
muscle-building training and training for injury prevention. Progress
Tracking, in conjunction with Performance Analytics, consolidates all
data from other components and feeds them into a sophisticated
analytical framework used to measure individual growth, consequently
giving output on a personalized training recommendation. In the end, the
proposed system aims to enable members to enjoy the maximum potential of
playing the sport, from the novice to the professional. The proposition
is really to create a platform that amalgamates advanced technology with
customization of skills and analytics for valid data that will focus on
improving basketball performances.
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