Background subtraction for realtime tracking of a tennis ball

In this paper we investigate real-time tracking of a tennis-ball using various image differencing techniques. First, we considered a simple background subtraction method with subsequent ball verification (BS). We then implemented two variants of our initial background subtraction method. The first is an image differencing technique that considers the difference in ball position between the current and previous frames along with a background model that uses a single Gaussian distribution for each pixel. The second is uses a mixture of Gaussians to accurately model the background image. Each of these three techniques constitutes a complete solution to the tennis ball tracking problem. In a detailed evaluation of the techniques in different lighting conditions we found that the mixture of Gaussians model produces the best quality tracking. Our contribution in this paper is the observation that simple background subtraction can outperform more sophisticated techniques on difficult problems, and we provide a detailed evaluation and comparison of the performance of our techniques, including a breakdown of the sources of error.