Ray Saliency: Bottom-Up Visual Saliency for a Rotating and Zooming Camera

Abstract

We extend the classical notion of computational visual saliency to multi-image data collected using a stationary pan-tilt-zoom (PTZ) camera by introducing the concept of consistency: the requirement that the set of generated saliency maps should each assign the same saliency value to unique regions of the environment that appear in more than one image. We show that processing each image independently will often fail to provide a consistent measure of saliency, and that using an image mosaic to quantify saliency suffers from several drawbacks. We then propose ray saliency and an immediate extension, approximate ray saliency: a mosaic-free method for calculating a consistent measure of bottom-up saliency. Experimental results demonstrating the effectiveness of the proposed approach are presented.