A comprehensive handball dynamics dataset for game situation classification.

ABSTRACT: This article presents a comprehensive dataset of labeled game situations obtained from multiple professional handball matches, which corresponds to the research paper entitled "PlayNet: Real-time Handball Play Classification with Kalman Embeddings and Neural Networks" [1]. The dataset encompasses approximately 11 hours of footage from five handball games played in two different arenas, resulting in around 1 million data frames. Each frame has been meticulously labeled using seven distinct game situation classes (left and right attacks, left and right transitions, left and right penalties, and timeouts). Notably, the dataset does not contain video frames, but provides a synthetic normalized representation of each frame. This representation includes information about player, referee, and bal

SUBMITTER: Mures OA 

PROVIDER: S-EPMC10749262 | biostudies-literature | 2024 Feb

REPOSITORIES: biostudies-literature