|Table of Contents|

A Novel Saliency Region Detection Algorithm(PDF)

《南京师大学报（自然科学版）》[ISSN:1001-4616/CN:32-1239/N]

Issue:
2012年03期
Page:
134-137
Research Field:
计算机科学
Publishing date:

Info

Title:
A Novel Saliency Region Detection Algorithm
Author(s):
Ye Cong1; Shen Jinlong2
1.Department of Computer Science,Suzhou College of Information Technology,Suzhou 215200,China
Keywords:
visual saliency; Bayes’theorem; central bias; neural network
PACS:
TP391.41
DOI:
-
Abstract:
A visual saliency detection method based on Bayes’theorem and statistical learning is proposed in this paper． The method clarifies different feature likelihood and different location prior for bottom-up saliency and overall saliency in static images based on Bayes’theorem． For feature integration problem，a weighted linear combination method using logistic model，and a weighted non-linear combination method using regularized neural network are used to learn the weight parameters to combine all factors． Experimental results demonstrate that our method’s bottom-up saliency maps perform better than other state-of-the-art saliency models in two fixation data sets by the metric receiver operator characteristic ( ROC) curve． And the extensive quantitative evaluation also demonstrates that the non-linear combination outperforms the linear combination strategy．

References:

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Last Update: 2013-03-11