Robust ball tracking scheme for soccer robot under various illuminations and occlusions

Abstract

The ball tracking method for soccer robot usually done using simple color thresholding and shape detection. The method is designed solely to track specific type of ball determined by the soccer robot regulation. However, the method should be robust and not to be limited to the regulation. In this research, a robust ball tracking method for soccer robot that can afford to track various types of ball under various illuminations and occlusions is developed. The proposed method uses combination of Histogram of Oriented Gradients (HOG) and Linear Support Vector Machine (Linear-SVM) to detect the ball and Optical Flow to track the ball. In order to reduce the computation, the method only scans the whole scene when the ball is not detected. Once the ball is detected, the method only scans the area around previously detected ball. HOG itself has its own mechanism to handle various illuminations and SVM as machine learning method is tolerance to occlusion. The experiment shows that the proposed scheme is accurate and can perform real time.