title: Team activity recognition in Association Football using a Bag-of-Words-based method.
abstract: In this paper, a new methodology is used to perform team activity recognition and analysis in Association Football. It is based on pattern recognition and machine learning techniques. In particular, a strategy based on the Bag-of-Words (BoW) technique is used to characterize short Football video clips that are used to explain the team's performance and to train advanced classifiers in automatic recognition of team activities. In addition to the neural network-based classifier, three more classifier families are tested: the k-Nearest Neighbor, the Support Vector Machine and the Random Forest. The results obtained show that the proposed methodology is able to explain the most common movements of a team and to perform the team activity recognition task with high accuracy when classifying three Football actions: Ball Possession, Quick Attack and Set Piece. Random Forest is the classifier obtaining the best classification results.
authors: Institute of New Imaging Technologies (INIT), Jaume I University, Castellón, Spain. Electronic address: montoliu@uji.es.
authors: Raúl
authors: R
authors: Montoliu
authors: Institute of New Imaging Technologies (INIT), Jaume I University, Castellón, Spain. Electronic address: martinr@uji.es.
authors: Raúl
authors: R
authors: Martín-Félez
authors: Institute of New Imaging Technologies (INIT), Jaume I University, Castellón, Spain. Electronic address: jtorres@uji.es.
authors: Joaquín
authors: J
authors: Torres-Sospedra
authors: Institute of New Imaging Technologies (INIT), Jaume I University, Castellón, Spain. Electronic address: auso@uji.es.
authors: Adolfo
authors: A
authors: Martínez-Usó
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D054874:Athletic Performance; D006801:Humans; D009038:Motion; D016571:Neural Networks, Computer; D010363:Pattern Recognition, Automated; D012916:Soccer; D060388:Support Vector Machine
keywords: Association Football; Bag-of-Words; Pattern recognition; Sport analysis; Team activity recognition