A two-stage approach to highlight extraction in sports video by using AdaBoost and multi-modal

Abstract

In this paper, we propose a novel two-stage approach for highlight extraction in sports video. In the first stage, a preliminary classification is performed to the audio stream to locate the position of the highlight candidates. We employ AdaBoost algorithm for feature selection and audio classification. In the second stage, we extract visual and temporal features of these highlight candidates and feed them into a linear weighted model for further highlight extraction. The final highlight segments are determined based on the output value of the model. The advantage of this method is its low computational complexity and relatively high accuracy. Experimental results on tennis video demonstrate effectiveness and efficiency of our proposed approach. © 2008 Springer.