Classifying and learning cricket shots using camera motion

Abstract

This paper presents a method to classify and learn cricket shots. The procedure begins by extracting the camera motion peirameters from the shots. Then the camera parameter values are converted to symbohc form and combined to generate a symbolic description that defines the trajectory of the cricket ball. The description generated is used to classify the cricket shot and to dynamically expeind or update the system’s knowledge of shots. The first novel aspect of this approeich is that by using the camera motion parameters, a complex and diflficult process of low level image segmenting of either the batsman or the cricket ball from video images is avoided. Also the method does not require high resolution images. Another novel aspect of this work is the use of a new incremental learning algorithm that enables the system to improve and update its knowledge base. Unlike previously developed algorithms which store training instances and have simple method to prime their concept hierarchies, the incremental learning algorithm used in this work generates compeict concept hiereirchies and uses evidence based forgetting. The results show that the system performs well in the task of classifying four types of cricket shots.