We present a system for automatically detecting salient image regions in stereoscopic videos. This report extends our previous system [4] and provides additional details about its implementation. Our proposed algorithm considers information based on three dimensions: salient colors in individual frames, salient information derived from camera and object motion, and depth saliency. These three c...

Visual system of human beings does not process the complete area of image rather focus upon limited area of visual image. But in which area does the visual attention focused is a topic of hot research nowadays. Research on psychological phenomenon indicates that attention is attracted to features that differ from its surroundings or the one that are unusual or unfamiliar to the human visual sys...

There is considerable controversy about whether salient singletons capture attention in a bottom-up fashion, irrespective of top-down control settings. One possibility is that salient singletons always generate an attention capture signal, but this signal can be actively suppressed to avoid capture. In the present study, we investigated this issue by using event-related potential recordings, fo...

The selection of salient regions in an image is the first step in many computer vision algorithms, e.g. objects recognition, classification or tracking. Our hypothesis is that local image statistics are indicative for saliency. We combine natural image statistics with the detection of salient regions. Particularly, we consider the integrated Weibull distribution as a parameterized model, which ...

We develop a new automatic Object of Interest detection method for image trimming and a novel tracking technique in active videos. Both applications consist of salient region detection and feature matching. We deploy a color-saliency weighted Probability-of-Boundary (cPoB) map to detect salient regions. Scale Space Image Pyramid (SSIP) feature matching is proposed for image trimming. An image p...

Object-based visual attention has received an increasing interest in recent years. Perceptual object is the basic attention unit of object-based visual attention. The definition and extraction of perceptual objects is one of the key technologies in object-based visual attention computation model. A novel perceptual object definition and extraction method is proposed in this paper. Based on Gest...

As a newly emerging and significant topic in computer vision community, co-saliency detection aims at discovering the common salient objects in multiple related images. The existing methods often generate the co-saliency map through a direct forward pipeline which is based on the designed cues or initialization, but lack the refinement-cycle scheme. Moreover, they mainly focus on RGB image and ...

This paper proposes an unsupervised bottom-up saliency detection approach by aggregating complementary background template with refinement. Feature vectors are extracted from each superpixel to cover regional color, contrast and texture information. By using these features, a coarse detection for salient region is realized based on background template achieved by different combinations of bound...

We investigated whether the deployment of attention in scenes is better explained by visual salience or by cognitive relevance. In two experiments, participants searched for target objects in scene photographs. The objects appeared in semantically appropriate locations but were not visually salient within their scenes. Search was fast and efficient, with participants much more likely to look to...

Measuring image similarity is important for a number of image processing applications. The goal of research in objective image similarity assessment is to develop quantitative measures that can automatically predict perceived image similarity. In this paper, we propose a new objective approach of measuring image similarity based on shape context. We take the geometric structures of objects into...