Evaluating the performance of two computer vision techniques for a mobile humanoid agent acting at Robocup kidsized soccer league
Nenhuma Miniatura disponível
Citações na Scopus
0
Tipo de produção
Artigo de evento
Data
2016-10-31
Autores
VILAO, C. O.
FERREIRA, V. N.
CELIBERTO, L. A.
Reinaldo Bianchi
FERREIRA, V. N.
CELIBERTO, L. A.
Reinaldo Bianchi
Orientador
Periódico
Communications in Computer and Information Science
Título da Revista
ISSN da Revista
Título de Volume
Citação
VILAO, C. O.; FERREIRA, V. N.; CELIBERTO, L. A.; BIANCHI, R. Evaluating the performance of two computer vision techniques for a mobile humanoid agent acting at Robocup kidsized soccer league. Communications in Computer and Information Science, v. 619, p. 1-19, Oct. 2016.
Texto completo (DOI)
Palavras-chave
Resumo
© Springer International Publishing AG 2016.A humanoid robot capable of playing soccer needs to identify several objects in the soccer field in order to play soccer. The robot has to be able to recognize the ball, teammates and opponents, inferring information such as their distance and estimated location. In order to achieve this key requisite, this paper analyzes two descriptor algorithms, HAAR and HOG, so that one of them can be used for recognizing humanoid robots with less false positives alarms and with best frame per second rate. They were used with their respective classical classifiers, AdaBoost and SVM. As many different robots are available in RoboCup domain, the descriptor needs to describe features in a way that they can be distinguished from the background at the same time the classification has to have a good generalization capability. Although some limitations appeared in tests, the results were beyond expectations. Given the results, the chosen descriptor should be able to identify a mainly white-ball, which is clearly a simpler object. The results for ball detection were also quite interesting.