Accurate ball detection in soccer images using probabilistic analysis of salient regions
Automatic sport video analysis has became one of the most attractive research fields in the areas of computer vision and multimedia technologies. In particular, there has been a boom in soccer video analysis research. This paper presents a new multi-step algorithm to automatically detect the soccer ball in image sequences acquired from static cameras. In each image, candidate ball regions are selected by analyzing edge circularity and then ball patterns are extracted representing locally affine invariant regions around distinctive points which have been highlighted automatically. The effectiveness of the proposed methodologies is demonstrated through a huge number of experiments using real balls under challenging conditions, as well as a favorable comparison with some of the leading approaches from the literature.
ball detection interest point detection dictionary learning sparse feature representation naive bayes classification soccer ball pattern recognition