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Artificial Neural Network Applied to Soccer Field Reconstruction

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Autor(es):
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Lima, Felipe B. C. L. ; Doria, Fernando F. ; Real, Lucas ; Oliveira, Vinicius R. G. ; Takimoto, Rogerio Y. ; Sato, Andre K. ; Najafabadi, Hossein R. ; Tsuzuki, Fabio S. G. ; Tsuzuki, Marcos S. G. ; Tsuzuki, MDG ; Pessoa, MAD
Número total de Autores: 11
Tipo de documento: Artigo Científico
Fonte: 2021 14TH IEEE INTERNATIONAL CONFERENCE ON INDUSTRY APPLICATIONS (INDUSCON); v. N/A, p. 5-pg., 2021-01-01.
Resumo

The 3D reconstruction and automatic statistical analysis of sporting events is an area of increasing demand and innovation. In this work, it is proposed the use of two different CNNs (AlexNet and LeNet) with different activation functions for the classification of soccer field view. The images will be classified as viewing the right goal, the center field, and the left goal. The classification of the soccer field view facilitates the creation of an automated algorithm for creating correspondences of relevant points. This activity is the most difficult to be automated. As it is very difficult to obtain real images for training the CNNs, it is proposed a method for creating synthetic soccer field views. Three CNNs presented good results and high accuracy. (AU)

Processo FAPESP: 20/02538-1 - Detecção dos jogadores e rastreamento da bola em cenas de partidas de futebol
Beneficiário:Fernando Ferreira Doria
Modalidade de apoio: Bolsas no Brasil - Iniciação Científica
Processo FAPESP: 19/03453-2 - Sensor inercial micro-eletro-mecânico para cidades inteligentes
Beneficiário:Hossein Rostami Najafabadi
Modalidade de apoio: Bolsas no Brasil - Doutorado