Abstract. Vision is a crucial sensor. It provides a very rich collection of information about our environment. However, not everything in a visual scene is relevant for the task at hand. Feature-based attention has been suggested for guiding vision towards the objects of interest in a visual search situation. Computational models of visual attention have implemented different concepts of feature-based attention. We will discuss these approaches and present a solution which is based on population-based inference. We illustrate the proposed mechanism with simulations using real world-scenes.