In this lecture we propose some methods to use computational models of visual attention for omnidirectional image classification. This lecture consists of two sections. In the first section, we propose a bottom-up model of visual attention for omnidirectional images and demonstrate its effectiveness in detecting robust regions in omnidirectional images. Afterward, we propose a top-down model of visual attention that benefits from spatial relations between scene objects to facilitate detection of the target object.