The classical hypothesis, that bottom-up saliency is a center-surround process, is combined
with a more recent hypothesis that all saliency decisions are optimal in a decision-theoretic …

Humans and other primates shift their gaze to allocate processing resources to a subset of
the visual input. Understanding and emulating the way that human observers free-view a …

Understanding how people explore immersive virtual environments is crucial for many
applications, such as designing virtual reality (VR) content, develo** new compression …

A novel Boolean Map based Saliency (BMS) model is proposed. An image is characterized
by a set of binary images, which are generated by randomly thresholding the image's color …

We present a generic objectness measure, quantifying how likely it is for an image window
to contain an object of any class. We explicitly train it to distinguish objects with a well …

Saliency prediction typically relies on hand-crafted (multiscale) features that are combined in
different ways to form a" master" saliency map, which encodes local image conspicuity …

For many applications in graphics, design, and human computer interaction, it is essential to
understand where humans look in a scene. Where eye tracking devices are not a viable …

Salient object detection is not a pure low-level, bottom-up process. Higher-level knowledge
is important even for task-independent image saliency. We propose a unified model to …

We address the issue of visual saliency from three perspectives. First, we consider saliency
detection as a frequency domain analysis problem. Second, we achieve this by employing …

We propose a definition of saliency by considering what the visual system is trying to
optimize when directing attention. The resulting model is a Bayesian framework from which …