This paper evaluates the degree of saliency of texts in natural scenes using visual saliency models. A large scale scene image database with pixel level ground truth is created for this purpose. Using this scene image database and five state-of-the-art models, visual saliency maps that represent the degree of saliency of the objects are calculated. The receiver operating characteristic curve is...

The classical hypothesis, that bottom-up saliency is a center-surround process, is combined with a more recent hypothesis that all saliency decisions are optimal in a decision-theoretic sense. The combined hypothesis is denoted as discriminant center-surround saliency, and the corresponding optimal saliency architecture is derived. This architecture equates the saliency of each image location t...

Depth information has been shown to affect identification of visually salient regions in images. In this paper, we investigate the role of depth in saliency detection in the presence of (i) competing saliencies due to appearance, (ii) depth-induced blur and (iii) centre-bias. Having established through experiments that depth continues to be a significant contributor to saliency in the presence ...

In this paper we are interested in the saliency of visual content from wearable cameras. The subjective saliency in wearable video is studied first due to the psycho-visual experience on this content. Then the method for objective saliency map computation with a specific contribution based on geometrical saliency is proposed. Fusion of spatial, temporal and geometric cues in an objective salien...

In computer vision saliency detection comprises wide range of methods to detect salient object present in the image. These methods focus how important object can be detect from the image. Results of these methods are fully dependent upon the type and quality of input image. In this paper saliency detection methods, Fixation prediction models, saliency map generated through various saliency dete...

Top-down saliency models produce a probability map that peaks at target locations specified by a task/goal such as object detection. They are usually trained in a fully supervised setting involving pixel-level annotations of objects. We propose a weakly supervised top-down saliency framework using only binary labels that indicate the presence/absence of an object in an image. First, the probabi...

Multiple redundant acoustic cues can contribute to the perception of a single phonemic contrast. This study investigated the effect of spectral degradation on the discriminability and perceptual saliency of acoustic cues for identification of word-final fricative voicing in "loss" versus "laws", and possible changes that occurred when low-frequency acoustic cues were restored. Three acoustic cu...

Salient object detection is a long-standing problem in computer vision and plays a critical role in understanding the mechanism of human visual attention. In applications that require object-level prior (e.g. image retargeting), it is desirable that saliency detection highlights holistic objects. Lately over-segmentation techniques such as SLIC superpixel [6], Meanshift [1], and graph-based [3]...

The lighting up of buildings is one form entertainment that makes a city more colorful, and photographers sometimes change this using photo-editing applications. This paper proposes method for automatically performing such changes follows the Retinex theory. theory indicates complex scenes caught by human visual system are affected surrounding colors, Retinex-based image processing uses these c...