In order to solve the problem of automatic detection of artificial objects in high resolution remote sensing images, a method for detection of artificial areas in high resolution remote sensing images based on multi-scale and multi feature fusion is proposed. Firstly, the geometric features such as corner, straight line and right angle are extracted from the original resolution, and the pseudo ...

Saliency detection is a well researched problem in computer vision. In previous work, most of the effort is spent on manually devising a saliency measure. Instead we propose a simple algorithm that uses a dataset with manually marked salient objects to learn to detect saliency. Building on the recent success of segmentation-based approaches to object detection, our saliency detection is based o...

Image matting aims at extracting foreground from a given image by means of color and alpha estimation. An automatic matting method based on saliency detection was proposed in this paper, which takes the advantages of saliency detection as prior information instead of user interaction. After getting the saliency map, a cost function was constructed to obtain an alpha matte. Moreover, with the in...

In this study, the authors investigated how salient visual features capture attention and facilitate detection of emotional facial expressions. In a visual search task, a target emotional face (happy, disgusted, fearful, angry, sad, or surprised) was presented in an array of neutral faces. Faster detection of happy and, to a lesser extent, surprised and disgusted faces was found both under upri...

Deep learning based salient object detection has recently achieved great success with its performance greatly outperforms any other unsupervised methods. However, annotating per-pixel saliency masks is a tedious and inefficient procedure. In this paper, we note that superior salient object detection can be obtained by iteratively mining and correcting the labeling ambiguity on saliency maps fro...

We propose a novel image retrieval framework for visual saliency detection using information about salient objects contained within bounding box annotations for similar images. For each test image, we train a customized SVM from similar example images to predict the saliency values of its object proposals and generate an external saliency map (ES) by aggregating the regional scores. To overcome...

The paper contributes to No-Reference video quality assessment of broadcasted HD video over IP networks and DVB. In this work we have enhanced our bottom-up spatio-temporal saliency map model by considering semantics of the visual scene. Thus we propose a new saliency map model based on face detection that we called semantic saliency map. A new fusion method has been proposed to merge the botto...

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...

The quantification of object saliency in 2D greyscale images is of primary importance in medical imaging. Saliency, in this paper, refers to the detectability of objects of unknown location, an object being a feature of interest in an image. Object saliency is commonly measured by the speed of an observer at performing a detection task. The more salient an object is, the more quickly it can be ...

As a component of low-level vision processing, saliency detection facilitates subsequent processing such as object detection or recognition. In this paper, we argue that a reasonable saliency detector should have the ability to: (1) Detect both small and large saliency regions. The size of salient regions vary greatly. When the salient region is large, however, because center-surround algorithm...