This paper proposes an automatic framework for figure-ground segmentation of edged images in the presence of cluttered background. Our work employs perceptual grouping concepts to characterize image segments by means of their saliency, which is computed via tensor voting. The main innovation of our work is a case-based thresholding scheme which iteratively eliminates edge segments with low-sali...

Saliency detection has drawn a lot of attention of researchers in various fields over the past several years. Saliency is the perceptual quality that makes an object, person to draw the attention of humans at the very sight. Salient object detection in an image has been used centrally in many computational photography and computer vision applications like video compression [1], object recogniti...

The human visual system has a remarkable ability to automatically attend to only salient regions, known as focus of attention in complex scenes. This ability enables us to allocate limited perceptual and cognitive resources on task relevant visual input. It is well known that attention also plays an important role when humans perceive visual quality of images. The goal of machine vision systems...

In a figure identification task, we investigated the influence of different visual cue configurations (spatial frequency, orientation or a combination of both) on the human EEG. Combining psychophysics with ERP and time-frequency analysis, we show that the neural response at about 200ms reflects perceptual saliency rather than physical cue contrast. Increasing saliency caused (i) a negative shi...

Visual saliency is an effective tool for perceptual image processing. In the past decades, many saliency models have been proposed by primarily considering visual cues such as local contrast and global rarity. However, such explicit cues derived only from input stimuli are often insufficient to separate targets from distractors, leading to noisy saliency maps. In fact, the latent cues, especial...

This paper extends an existing saliency-based model for path detection and tracking so that the appearance of the path being followed can be learned and used to bias the saliency computation process. The goal is to reduce ambiguities in the presence of strong distractors. In both original and extended path detectors, neural and swarm models are layered in order to attain a hybrid solution. With...

Given the lack of a standardized evaluation system for infrared jamming effectiveness false targets, this paper first uses co-saliency detection model to extract main parts true and targets. Then perceptual similarity algorithm is improved by combining operational requirements targets in band. Finally, background-independent constructed. The experimental results show that can quantitatively ref...

We examined the ability of older adults to select local and global stimuli varying in perceptual saliency-a task requiring nonspatial visual selection. Participants were asked to identify in separate blocks a target at either the global or the local level of a hierarchical stimulus, while the saliency of each level was varied (across different conditions, either the local or the global form was...