Football Player Detection in Video Broadcast

The paper describes a novel segmentation system based on the combination of Histogram of Oriented Gradients (HOG) descriptors and linear Support Vector Machine (SVM) classification for football video. Recently, HOG methods were widely used for pedestrian detection. However, presented experimental results show that combination of HOG and SVM is very promising for locating and segmenting players. In proposed system a dominant color based segmentation for football playfield detection and a 3D playfield modeling based on Hough transform is introduced. Experimental evaluation of the system is done for SD (720×576) and HD (1280×720) test sequences. Additionally, we test proposed system performance for different lighting conditions (non-uniform pith lightning, multiple player shadows) as well as for various positions of the cameras used for acquisition.