English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

In this paper, we propose a new visual saliency detection method, which is effective regardless of unreliable disparity information, by using contrast and prior knowledge. Our proposed method consists of two phases. In the first phase, we used region based contrast information to compute the saliency of an input image. We consider not only global but also local contrast in color and disparity information to efficiently extract salient regions in a stereoscopic image. In addition, we introduce a confidence measure to handle unreliable disparity information. In the second phase, we used region based prior knowledge existent in a stereoscopic image. The region based prior knowledge is constructed from low-level features such as color, frequency, location and disparity in the stereoscopic image. Finally, we integrate contrast-based and prior knowledge-based saliency to accurately detect saliency from input stereoscopic image. Experimental results show that our method efficiently detects salient contents in stereoscopic images.

A New Saliency Detection Method for Stereoscopic Images Using Contrast and Prior Knowledge