Detecting salient objects from images and videos has many useful applications in computer vision. In this paper, a novel spatiotemporal salient region detection approach is proposed. The proposed approach computes spatiotemporal saliency by estimating spatial and temporal saliencies separately. The spatial saliency is computed estimating of color contrast cue and color distribution cue by explo...

Recently, saliency detection in a single image and co-saliency detection in multiple images have drawn extensive research interest in the vision community. In this paper, we investigate a new problem of co-saliency detection within a single image, i.e., detecting within-image co-saliency. By identifying common saliency within an image, e.g., highlighting multiple occurrences of an object class ...

In this paper, we present a video saliency detection method by spatio-temporal sampling and sparse matrix decomposition. In the method, we sample the input video sequence into three planes: X-T slice plane, YT slice plane, and X-Y slice plane. Then, motion saliency map is extracted from the X-T and Y-T slices, and static saliency map is extracted from the X-Y slices by low-rank matrix decomposi...

Visual salience detection originated over 500 million years ago and is one of nature’s most efficient mechanisms. In contrast, many state-of-the-art computational saliency models are complex and inefficient. Most saliency models process high-resolution color (HC) images; however, insights into the evolutionary origins of visual salience detection suggest that achromatic low-resolution vision is...

This paper proposes an unsupervised bottom-up saliency detection approach by aggregating complementary background template with refinement. Feature vectors are extracted from each superpixel to cover regional color, contrast and texture information. By using these features, a coarse detection for salient region is realized based on background template achieved by different combinations of bound...

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...

Saliency maps as visual attention computational models can reveal novel regions within a scene (as in the human visual system), which can decrease the amount of data to be processed in task specific computer vision applications. Most of the saliency computation models do not take advantage of prior spatial memory by giving priority to spatial or object based features to obtain bottom-up or top-...

In this paper, we present an image saliency detection method by constructing graph model. We extract color, texture and compactness features and segment superpixels from an input image to construct a graph model. Then, saliency for each is measured by calculating random walker probability on the node. Extensive results on MSRA dataset containing 1000 test images with ground truths demonstrate t...