Salient region detection using local and global saliency

Yiu Ming Cheung*, Qinmu Peng

*Corresponding author for this work

Research output: Chapter in book/report/conference proceedingConference proceedingpeer-review

3 Citations (Scopus)

Abstract

In this paper, we present a novel local-global salient region detection method. We first obtain the smoothed image via gradient minimization, resulting in more homogeneous background. Then, we partition the smoothed image into a set of regions and compute the region saliency by measuring the dissimilarity and spatial distance. Furthermore, we adopt the global color distribution, including the color coherence, to yield global saliency region. Finally, we combine the local-and-global salient regions and the composition information to obtain the overall salient regions. Experimental results show the efficacy of the proposed method in comparison with the existing methods.

Original languageEnglish
Title of host publicationProceedings of the 21st International Conference on Pattern Recognition (ICPR2012)
PublisherIEEE
Pages210-213
Number of pages4
ISBN (Print)9784990644109
Publication statusPublished - Nov 2012
Event21st International Conference on Pattern Recognition, ICPR 2012 - Tsukuba, Japan
Duration: 11 Nov 201215 Nov 2012

Publication series

NameProceedings - International Conference on Pattern Recognition
ISSN (Print)1051-4651

Conference

Conference21st International Conference on Pattern Recognition, ICPR 2012
Country/TerritoryJapan
CityTsukuba
Period11/11/1215/11/12

Scopus Subject Areas

  • Computer Vision and Pattern Recognition

Fingerprint

Dive into the research topics of 'Salient region detection using local and global saliency'. Together they form a unique fingerprint.

Cite this