Playfield detection using adaptive GMM and its application
Playfield detection is a key step in sports video content analysis, since many semantic clues could be inferred from it. In this paper we propose an adaptive GMM based algorithm for playfield detection. Its advantages are twofold. First, it can update model parameters by the incremental expectation maximization (IEM) algorithm, which enables the model to adapt to the playfield variation with time; Second, online training is performed, which saves buffer for training samples. Then, the playfield detection results are applied in recognizing the key zone of the current playfield in soccer video, in which a fast algorithm based on playfield contour and least square is proposed. Experimental results show that the proposed algorithms are encouraging.