Visual saliency detection model simulates the human visual system to perceive the scene, and has been widely used in many vision tasks. With the acquisition technology development, more comprehensive information, such as depth cue, inter-image correspondence, or temporal relationship, is available to extend image saliency detection to RGBD saliency detection, co-saliency detection, or video sal...

Co-saliency detection is a newly emerging and rapidly growing research area in computer vision community. As a novel branch of visual saliency, co-saliency detection refers to the discovery of common and salient foregrounds from two or more relevant images, and can be widely used in many computer vision tasks. The existing co-saliency detection algorithms mainly consist of three components: ext...

The success of current deep saliency detection methods heavily depends on the availability of large-scale supervision in the form of per-pixel labeling. Such supervision, while labor-intensive and not always possible, tends to hinder the generalization ability of the learned models. By contrast, traditional handcrafted features based unsupervised saliency detection methods, even though have bee...

—Traditional saliency models usually adopt hand-crafted image features and human-designed mechanisms to calculate local or global contrast. In this paper, we propose a novel computational saliency model, i.e., deep spatial contextual long-term recurrent convolutional network (DSCLRCN) to predict where people looks in natural scenes. DSCLRCN first automatically learns saliency related local feat...

Our visual system can link components of contours and segregate contours from complex backgrounds based on geometric grouping rules. This is an important intermediate step in object recognition. The substrate for contour integration may be based on contextual interactions and intrinsic horizontal connections seen in primary visual cortex (V1). We examined the perceptual rules governing contour ...

Video saliency detection (VSD) aims at fast locating the most attractive objects/things/patterns in a given video clip. Existing VSD-related works have mainly relied on visual system but paid less attention to audio aspect. In contrast, our is vital complementary part of system. Also, audio-visual (AVSD), one representative research topics for mimicking human perceptual mechanisms, currently it...

The visual system uses continuity as a cue for grouping oriented line segments that define object boundaries in complex visual scenes. Many studies support the idea that long-range intrinsic horizontal connections in early visual cortex contribute to this grouping. Top-down influences in primary visual cortex (V1) play an important role in the processes of contour integration and perceptual sal...

Patients with Balint' s syndrome are typically impaired at perceiving multiple objects simultaneously, and at evaluating the relationship between multiple objects in a scene (simultanagnosia). These deficits may not only be observed in complex scenes, but also when local elements of individual objects must be integrated into a perceptual global whole. Thus, unlike normal observers, patients wit...

feature extraction is a main step in all perceptual image hashing schemes in which robust features will led to better results in perceptual robustness. simplicity, discriminative power, computational efficiency and robustness to illumination changes are counted as distinguished properties of local binary pattern features. in this paper, we investigate the use of local binary patterns for percep...

Objective image quality metrics (IQMs) potentially benefit from the addition of visual saliency. However, challenges to optimising the performance of saliency-based IQMs remain. A previous eye-tracking study has shown that gaze is concentrated in fewer places in images with highly salient features than in images lacking salient features. From this, it can be inferred that the former are more li...