Title :
Saliency Detection: A Spectral Residual Approach
Author :
Hou, Xiaodi ; Zhang, Liqing
Author_Institution :
Shanghai Jiao Tong Univ., Shanghai
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;
Conference_Titel :
Computer Vision and Pattern Recognition, 2007. CVPR '07. IEEE Conference on
Conference_Location :
Minneapolis, MN
Print_ISBN :
1-4244-1179-3
Electronic_ISBN :
1063-6919
DOI :
10.1109/CVPR.2007.383267