Basketball free throw hit probability prediction system based on deep learning object detection and pose estimation
Year: 2025
Type: article
Abstract: With the rapid progress of artificial intelligence, deep learning technology has been extensively adopted in sports. As a key scoring point in basketball games, accurately predicting and analyzing the trajectory of arm movements is crucial for enhancing the hit rate of free throws. Therefore, to improve the prediction probability of free throws in basketball games, a spatial transformation module is used to optimize the extraction accuracy of object detection in densely populated sports venues. In addition, the study also utilizes a three-dimensional pose estimation algorithm to predict the vector field of joint key points and joint connections. The accuracy in predicting the angle of the shooting arm and the angle of the take-off leg reached 92.06% and 91.12%, respectively. In summary, the designed system has effectively improved the hit probability of basketball free throws.
Source: Systems and Soft Computing
Author: Hao Deng
Institution: Xi'an Jiaotong University City College
Language: English
Subfield: Computer Vision and Pattern Recognition
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $1,870
OpenAlex ID: W4411342116