DocumentCode
3017990
Title
Saliency Detection: A Spectral Residual Approach
Author
Hou, Xiaodi ; Zhang, Liqing
Author_Institution
Shanghai Jiao Tong Univ., Shanghai
fYear
2007
fDate
17-22 June 2007
Firstpage
1
Lastpage
8
Abstract
The ability of human visual system to detect visual saliency is extraordinarily fast and reliable. However, computational modeling of this basic intelligent behavior still remains a challenge. This paper presents a simple method for the visual saliency detection. Our model is independent of features, categories, or other forms of prior knowledge of the objects. By analyzing the log-spectrum of an input image, we extract the spectral residual of an image in spectral domain, and propose a fast method to construct the corresponding saliency map in spatial domain. We test this model on both natural pictures and artificial images such as psychological patterns. The result indicate fast and robust saliency detection of our method.
Keywords
feature extraction; object detection; artificial images; features independent; image log-spectrum; intelligent behavior; psychological patterns; saliency detection; spatial domain; spectral domain; spectral residual approach; Computational modeling; Humans; Image analysis; Image coding; Machine vision; Object detection; Object recognition; Redundancy; Statistical distributions; Visual system;
fLanguage
English
Publisher
ieee
Conference_Titel
Computer Vision and Pattern Recognition, 2007. CVPR '07. IEEE Conference on
Conference_Location
Minneapolis, MN
ISSN
1063-6919
Print_ISBN
1-4244-1179-3
Electronic_ISBN
1063-6919
Type
conf
DOI
10.1109/CVPR.2007.383267
Filename
4270292
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