Salient region detection using a discriminative color transform dictionary = 차별적 색상 변환 사전을 이용한 관심 영역 검출

Cited 0 time in webofscience Cited 0 time in scopus
  • Hit : 217
  • Download : 0
Salient region detection is a process of extracting a visually attractive region from a single image. In this paper, we present a novel method for automatically detecting salient region with discriminative color transform dictionary. The key assumption of the proposed framework is that the saliency map can be represented as a linear combination of color components of an image. To find a set of optimal coefficients for this linear combination, we incorporate least squares with constructing color transform dictionary, which includes multiple powers of color components in RGB and CIELab color space. In addition, we refine the saliency map by solving sparse representation problem with local dictionary, which is intended to enhance the compactness of the salient region in the saliency map. Experimental results show that the proposed method provides the saliency maps of two benchmark datasets with better quality and improved performance, compared to the previous state-of-the-art techniques.
Advisors
Kim, Junmoresearcher김준모researcher
Description
한국과학기술원 :전기및전자공학과,
Publisher
한국과학기술원
Issue Date
2013
Identifier
325007
Language
eng
Description

학위논문(석사) - 한국과학기술원 : 전기및전자공학과, 2013.8 ,[v, 33 p. :]

Keywords

saliency detection; compactness; least-squares; dictionary learning; color space; 관심 영역 검출; 조밀도; 최소자승법; 사전 학습; 색상 공간

URI
http://hdl.handle.net/10203/221695
Link
http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=657348&flag=dissertation
Appears in Collection
EE-Theses_Master(석사논문)
Files in This Item
There are no files associated with this item.

qr_code

  • mendeley

    citeulike


rss_1.0 rss_2.0 atom_1.0