This paper presents a novel method for detecting saliency in static images based on image sparse representation. For each color channel, first, the image is partitioned into non-overlapping patches and each patch is represented by the way of sparse coding from a learned dictionary of patches from natural scenes. Then, global saliency and local saliency are calculated and fused to attain salienc...

generally human vision system searches for salient regions and movements in video scenes to lessen the search space and effort. using visual saliency map for modelling gives important information for understanding in many applications. in this paper we present a simple method with low computation load using visual saliency map for background subtraction in video stream. the proposed technique i...

To aim at the defect that the classic significant region detection algorithm IG suppresses the most significant pixels, a novel saliency detection method combined with neighborhood inhomogeneity factor NIF is put forward. This algorithm achieves the satisfying result in static image saliency detection. Firstly, IG saliency map is obtained according to the IG algorithm, and then the NIF saliency...

Salient region detection is important for many high-level computer vision tasks. The majority of previous works exploit element contrast to detect image saliency region. In this paper, we propose a novel approach to analyze saliency cues from multiple scales of image structure, using a multi-scale image abstraction. In each image layer global color contrast cue and color spatial distribution cu...

This paper proposes a novel saliency detection method by combining region-level saliency estimation and pixel-level saliency prediction with CNNs (denoted as CRPSD). For pixel-level saliency prediction, a fully convolutional neural network (called pixel-level CNN) is constructed by modifying the VGGNet architecture to perform multiscale feature learning, based on which an image-to-image predict...

Saliency map detection, as a method for detecting important regions of an image, is used in many applications such as image classification and recognition. We propose that context detection could have an essential role in image saliency detection. This requires extraction of high level features. In this paper a saliency map is proposed, based on image context detection using semantic segmentati...

An efficient modified video compression HEVC technique based on high quality assessment saliency features presented for the assessment of high quality videos. To create an efficient saliency map we extract global temporal alignment component and robust spatial components. To obtain high quality saliency here, we combine spatial saliency features and temporal saliency features together for diffe...

In contrast to the wealth of saliency models in the vision literature, there is a relative paucity of models exploring auditory saliency. In this work, we integrate the approaches of (Kayser, Petkov, Lippert, & Logothetis, 2005) and (Zhang, Tong, Marks, Shan, & Cottrell, 2008) and propose a model of auditory saliency. The model combines the statistics of natural soundscapes and the recent past ...

In this paper, we introduce a biologically-motivated model to detect image saliency. The model employs an isophote based operator to detect potential structure and global saliency information related to each pixel, which are then combined with integral image to build up final saliency maps. We show that the proposed model outperforms seven state-of-the-art saliency detectors in experimental stu...