Attention is intrinsic to our perceptual representations of sensory inputs. Best characterized in the visual domain, it is typically depicted as a spotlight moving over a saliency map that topographically encodes strengths of visual features and feedback modulations over the visual scene. By introducing smells to two well-established attentional paradigms, the dot-probe and the visual-search pa...

Salient parts of a visual scene attract longer and earlier fixations of the eyes. Saliency is driven by bottom-up (image dependent) factors and top-down factors such as behavioral relevance, goals, and expertise. It is currently assumed that a saliency map defining eye fixation priorities is stored in neural structures that remain to be determined. Lesion studies support a role for the amygdala...

Visual saliency is a fundamental yet hard to define property of objects or locations in the visual world. In a context where objects and their representations compete to dominate our perception, saliency can be thought of as the "juice" that makes objects win the race. It is often assumed that saliency is extracted and represented in an explicit saliency map, which serves to determine the locat...

We propose a novel efficient algorithm for computing visual saliency, which is based on the computation architecture of Itti model. As one of well-known bottom-up visual saliency models, Itti method evaluates three low-level features, color, intensity, and orientation, and then generates multiscale activation maps. Finally, a saliency map is aggregated with multiscale fusion. In our method, the...

Visual saliency computation is about detecting and understanding salient regions and elements in a visual scene. Algorithms for visual saliency computation can give clues to where people will look in images, what objects are visually prominent in a scene, etc. Such algorithms could be useful in a wide range of applications in computer vision and graphics. In this thesis, we study the following ...

Motion saliency map is a critical feature in rapid analysis of video data, especially in coping with visual information overload and cluttered background [1]. Its potential applications include automatic action recognition, recognition of moving objects, and target tracking [2, 3, 4]. Similar to the other feature saliency maps, a motion saliency map is a topographic representation of the motion...

The primate visual system continuously selects spatial proscribed regions, features or objects for further processing. These selection mechanisms--collectively termed selective visual attention--are guided by intrinsic, bottom-up and by task-dependent, top-down signals. While much psychophysical research has shown that overt and covert attention is partially allocated based on saliency-driven e...

Visual saliency prediction in computer vision aims at estimating the locations in an image that attract the attention of humans. A saliency map is a heatmap that represents the probability of each corresponding pixel in the image to capture human attention. These saliency maps have been used as soft-attention guides for other computer vision tasks, and also directly for user studies in fields l...

This paper is to present a Bayesian learning based framework for visual saliency detection in natural scenes. Especially, for any point in the scene, this framework has considered whether it is salient or not; but previous methods by Bayesian learning seem not to do so. This framework includes two steps. First, the framework indicates that visual saliency is constituted with three main saliency...

A recent development in the area of image quality consists of trying to incorporate aspects of visual attention in the metric design. This is generally achieved by combining distortion maps and saliency maps. Although a good number of saliency-inspired image quality metrics have been proposed, results are not yet conclusive. Some researchers have reported that the incorporation of visual attent...