Computational Visual Attention Systems

Abstract

Computational Visual attention systems (CVAS ) have gained a lot of interest during the last years. Similar to the human visual system, VSAS detect regions of interest in images: by “directing attention” to these regions, they restrict further processing to sub-regions of the image. Such guiding mechanisms are urgently needed, since the amount of information available in an image is so large that even the most performant computer cannot carry out exhaustive search on the data. Psychologists, neurobiologists, and computer scientists have investigated visual attention thoroughly during the last decades and profited considerably from each other. However, the interdisciplinary of the topic holds not only benefits but also difficulties.

This seminar provides an extensive survey of the grounding psychological and biological research on visual attention as well as the current state of the art of computational systems. It includes basic theories and models like Feature Integration Theory(FIT model) and Guided Search Model(GSM).A Real time Computational Visual Attention System VOCUS (Visual Object detection with a CompUtational attention System) is also included. Furthermore, presents a broad range of applications of computational attention systems in fields like computer vision, cognitive systems, and mobile robotics.