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Robust Swimming Style Classification from Color Video

We present a robust method to classify swimming styles from live video based on the features extracted from the upper-body of the swimmer. In our approach, potential body parts are first extracted using a simple skin color model. Next, the dominant components in the segmented regions are selected according to quantitative measures such as the aspect ratio and the area. Regression analysis is performed to calculate the relative position of the constituent body parts. Finally, a scoring system is constructed to carry out the classification. Experimental results demonstrate the validity and efficiency of our proposed approach.