Abstract
It is significant for the final goal of RoboCup to realize the recognition of generic balls for soccer robots. In this paper, a novel generic ball recognition algorithm based on omnidirectional vision is proposed by combining the modified Haar-like features and AdaBoost learning algorithm. The algorithm is divided into offline training and online recognition. During the phase of offline training, numerous sub-images are acquired from various panoramic images, including generic balls, and then the modified Haar-like features are extracted from them and used as the input of the AdaBoost learning algorithm to obtain a classifier. During the phase of online recognition, and according to the imaging characteristics of our omnidirectional vision system, rectangular windows are defined to search for the generic ball along the rotary and radial directions in the panoramic image, and the learned classifier is used to judge whether a ball is included in the window. After the ball has been recognized globally, ball tracking is realized by integrating a ball velocity estimation algorithm to reduce the computational cost. The experimental results show that good performance can be achieved using our algorithm, and that the generic ball can be recognized and tracked effectively.
Highlights
The ball is the chasing focus for soccer robots in the RoboCup Middle Size League (MSL) competition, so ball recognition is a research focus for MSL teams
A generic ball recognition algorithm based on our omnidirectional vision system was proposed by combining Haar-like features and the AdaBoost learning algorithm
During the offline training phase, the traditional Haar-like features were modified, and extracted from the sub-images for training and used as the input of the AdaBoost learning algorithm to acquire the classifier for recognizing generic balls
Summary
The ball is the chasing focus for soccer robots in the RoboCup Middle Size League (MSL) competition, so ball recognition is a research focus for MSL teams. Almost all of the robots can recognize the colour-coded balls, like the orange or yellow ball, effectively. Soccer robots should be able to recognize the generic FIFA balls with arbitrary colours or textures like human beings. This has become a challenging issue in the research into robot vision for RoboCup MSL soccer robots, because the traditional ball www.intechopen.com. SaynstX.,io2n0g13a,nVdoZlh. i1q0ia, n3g88Z:h2e0n1g3: 1 A Novel Generic Ball Recognition Algorithm Based on Omnidirectional Vision for Soccer Robots recognition methods based on colour classification [1, 2] cannot be used any more. A novel generic ball recognition algorithm is proposed for our NuBot soccer robots.
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