Saliency detection aims to detect the most attractive objects in images, which has been widely used as a foundation for various multimedia applications. In this paper, we propose a novel salient object detection algorithm for RGB-D images using center-dark channel prior. First, we generate an initial saliency map based on a color saliency map and a depth saliency map of a given RGB-D image. The...

Automatic estimation of salient object regions across images, without any prior assumption or knowledge of the contents of the corresponding scenes, enhances many computer vision and computer graphics applications. We introduce a regional contrast based salient object extraction algorithm, which simultaneously evaluates global contrast differences and spatial weighted coherence scores. The prop...

Despite significant progress, image saliency detection still remains a challenging task in complex scenes and environments. Integrating multiple different but complementary cues, like RGB and Thermal (RGB-T), may be an effective way for boosting saliency detection performance. The current research in this direction, however, is limited by the lack of a comprehensive benchmark. This work contrib...

Traditional saliency detection algorithms lack object semantic character, and the segmentation algorithms cannot highlight the saliency of the segmentation regions. In order to compensate for the defects of these two algorithms, the salient object segmentation model, which is a novel combination of two algorithms, is established in this paper. With the help of a priori knowledge of image bounda...

To detect visually salient elements of complex natural scenes, computational bottom-up saliency models commonly examine several feature channels such as color and orientation in parallel. They compute a separate feature map for each channel and then linearly combine these maps to produce a master saliency map. However, only a few studies have investigated how different feature dimensions contri...

Vehicle detection in remote sensing imagery is a challenging task because of its inherent attributes, e.g., dense parking, small sizes, various angles, etc. Prevalent vehicle detectors adopt an oriented/rotated bounding box as basic representation, which needs to apply distance regression height, width, and angles objects. These distance-regression-based suffer from two challenges: (1) the peri...

To detect and recognise hand postures against complex backgrounds, we propose a novel model that is constructed by the integration of image saliency and skin information. Although a skin model is a simple and efficient strategy by which to locate skin regions within images, it is easily affected by complex backgrounds, e.g. skin-like background regions and various lighting conditions. To solve ...

This paper brings forth a learning-based visual saliency model method for detecting diagnostic diabetic macular edema (DME) regions of interest (RoIs) in retinal image. The method introduces the cognitive process of visual selection of relevant regions that arises during an ophthalmologist's image examination. To record the process, we collected eye-tracking data of 10 ophthalmologists on 100 i...

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