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2016 | OriginalPaper | Chapter

Evaluating the Performance of Two Computer Vision Techniques for a Mobile Humanoid Agent Acting at RoboCup KidSized Soccer League

Authors : Claudio O Vilão Jr., Vinicius Nicassio Ferreira, Luiz Antonio Celiberto Jr., Reinaldo A. C. Bianchi

Published in: Robotics

Publisher: Springer International Publishing

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Abstract

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.

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next chapter Dense Tracking with Range Cameras Using Key Frames
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Metadata
Title
Evaluating the Performance of Two Computer Vision Techniques for a Mobile Humanoid Agent Acting at RoboCup KidSized Soccer League
Authors
Claudio O Vilão Jr.
Vinicius Nicassio Ferreira
Luiz Antonio Celiberto Jr.
Reinaldo A. C. Bianchi
Copyright Year
2016
Book
Robotics

Print ISBN: 978-3-319-47246-1

Electronic ISBN: 978-3-319-47247-8

Copyright Year: 2016

DOI
https://doi.org/10.1007/978-3-319-47247-8_1