Evaluation of shadow classification techniques for object detection and tracking

In a football stadium environment with multiple overhead floodlights, many protruding shadows can be observed orig-inating from each of the targets. To successfully track in-dividual targets, it is essential to achieve an accurate rep-resentation of the foreground. Many of the existing tech-niques are sensitive to shadows, falsely classifying shadows as foreground. This work presents four different techniques associated with shadow classification. Three of the classi-fier’s originate from the review material whilst the fourth is a novel application of a real-time implementation of the k-nearest neighbour algorithm to shadow identification. To assess the performance for each of the classifiers four quan-titative evaluation metrics are proposed. Using each of the evaluation metrics, we will discuss the performance of each classifier’s segmentation results as well as assess their im-pact on the tracking performances. 1