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Information × Registration Number 2120U007851, Article popup.category Препринт Title Basketball Pose-based Action Recognition (AI translated) popup.author Zakharchenko IrynaZakharchenko Iryna popup.publication 01-01-2020 popup.source_user Український католицький університет popup.source https://hdl.handle.net/20.500.14570/4488 popup.publisher Description Action detection on a team sport is a challenging task, while sports analysis is on-demand and in high interest. A great number of researchers try to make analysis automated. Despite enormous success in image classification using deep learning, action recognition in the video remains a difficult task, and at present no good solu- tion exists in terms of accuracy and speed. The main challenge in action recognition is to design architecture that will capture both spatial and temporal information. In team sports action analysis, the serious challenges are that we have multiple play- ers performing simultaneously different actions, the players are constantly moving, there are occlusions, the camera itself is moving. The proposed method is able to si- multaneously recognize the actions of multiple players using pose estimation, track- ing, and LSTM for action classification. popup.nrat_date 2025-11-05 Close