ACA-Net: adaptive context-aware network for basketball action recognition.

ABSTRACT: The advancements in intelligent action recognition can be instrumental in developing autonomous robotic systems capable of analyzing complex human activities in real-time, contributing to the growing field of robotics that operates in dynamic environments. The precise recognition of basketball players' actions using artificial intelligence technology can provide valuable assistance and guidance to athletes, coaches, and analysts, and can help referees make fairer decisions during games. However, unlike action recognition in simpler scenarios, the background in basketball is similar and complex, the differences between various actions are subtle, and lighting conditions are inconsistent, making action recognition in basketball a challenging task. To address this problem, an Adaptive Context

SUBMITTER: Zhang Y 

PROVIDER: S-EPMC11461453 | biostudies-literature | 2024

REPOSITORIES: biostudies-literature