A Biologically Inspired Saliency Priority Extraction Using Bayesian Framework

Jila Hosseinkhani and Chris Joslin
Additional contact information
Jila Hosseinkhani: Carleton University, Ottawa, Canada
Chris Joslin: Carleton University, Ottawa, Canada

International Journal of Multimedia Data Engineering and Management (IJMDEM), 2019, vol. 10, issue 2, 1-20

Abstract: In this article, the authors used saliency detection for video streaming problem to be able to transmit regions of video frames in a ranked manner based on their importance. The authors designed an empirically-based study to investigate bottom-up features to achieve a ranking system stating the saliency priority. We introduced a gradual saliency detection model using a Bayesian framework for static scenes under conditions that we had no cognitive bias. To extract color saliency, we used a new feature contrast in Lab color space as well as a k-nearest neighbor search based on k-d tree search technique to assign a ranking system into different colors according to our empirical study. To find the salient textured regions we employed contrast-based Gabor energy features and then we added a new feature as intensity variance map. We merged different feature maps and classified saliency maps using a Naive Bayesian Network to prioritize the saliency across a frame. The main goal of this work is to create the ability to assign a saliency priority for the entirety of a video frame rather than simply extracting a salient area which is widely performed.

Date: 2019
References: Add references at CitEc
Citations:

Downloads: (external link)
http://services.igi-global.com/resolvedoi/resolve. ... 18/IJMDEM.2019040101 (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:igg:jmdem0:v:10:y:2019:i:2:p:1-20

Access Statistics for this article

International Journal of Multimedia Data Engineering and Management (IJMDEM) is currently edited by Chengcui Zhang

More articles in International Journal of Multimedia Data Engineering and Management (IJMDEM) from IGI Global
Bibliographic data for series maintained by Journal Editor ().