Salient object detection in videos is challenging because of the competing motion in the background, resulting from camera tracking an object of interest, or motion of objects in the foreground. The authors present a fast method to detect salient video objects using particle filters, which are guided by spatiotemporal saliency maps and color feature with the ability to quickly recover from fals...

Salient object detection has seen remarkable progress driven by deep learning techniques. However, most of deep learning based salient object detection methods are black-box in nature and lacking in interpretability. This paper proposes the first self-explanatory saliency detection network that explicitly exploits lowand high-level features for salient object detection. We demonstrate that such...

Saliency detection has become a very prominent subject for research in recent time. Many techniques has been defined for the saliency detection.In this paper number of techniques has been explained that include the saliency detection from the year 2000 to 2015, almost every technique has been included.all the methods are explained briefly including their advantages and disadvantages. Comparison...

In this paper, a natural image compression method is proposed based on independent component analysis (ICA) and visual saliency detection. The proposed compression method learns basis functions trained from data using ICA to transform the image at first; and then sets percentage of the zero coefficient number in the total transforming coefficients. After that, transforming coefficients are spar...

New algorithms and architectures for the current industrial wireless sensor networks shall be explored to ensure the efficiency, robustness, and consistence in variable application environments which concern different issues, such as the smart grid, water supply, and gas monitoring. Object detection automatic in remote sensing images has always been a hot topic. Using the conventional deep conv...

Recent years have seen many complex models proposed for salient object detection and progressing results. However, less has been done to justify the need for such complex models as there lacks sufficient comparison to simple baselines on more challenging datasets. In this work, we propose a new baseline method for saliency detection. It simply considers a large region close to the image center ...

We propose an efficient regional histogram (RH)-based computation model for saliency detection in natural images. First, the global histogram is constructed by performing an adaptive color quantization on the original image. Then multiple RHs are built on the basis of the region segmentation result, and the color-spatial similarity between each pixel and each RH is calculated accordingly. Two e...

This paper presents a new hybrid approach for detecting salient objects in an image. It consists of two processes: local saliency estimation and global-homogeneity refinement. We model the salient object detection problem as a region growing and competition process by propagating the influence of foreground and background seed-patches. First, the initial local saliency of each image patch is me...

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...

Saliency detection is a useful tool for video-based, real-time Computer Vision applications. It allows to select which locations of the scene are the most relevant and has been used in a number of related assistive technologies such as life-logging, memory augmentation and object detection for the visually impaired, as well as to study autism and the Parkinson’s disease. Many works focusing on ...