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 originating from each of the targets. To successfully track individual targets, it is essential to achieve an accurate representation of the foreground. Many of the existing techniques are sensitive to shadows, falsely classifying shadows as foreground. This work presents four different techniques associated with shadow classification. Three of the classifier'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 quantitative 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 impact on the tracking performances.

• Type: Conference
• Year: 2004
• Where: ICIP
• Authors: John-Paul Renno, James Orwell, Graeme A. Jones
• Keywords: Football Stadium Environment, ICIP 2004, Image Processing, Individual Targets, K-nearest Neighbour Algorithm, Multiple Overhead Floodlights, Quantitative Evaluation Metrics