Saliency detection based on 2D log-gabor wavelets and center bias

Authors:
Min Wang;Jia Li;Tiejun Huang;Yonghong Tian;Lingyu Duan;Guochen Jia
Affiliations:
National Engineering Laboratory for Video Technology (NELVT), School of EE & CS, Peking University, Beijing 100871, China, Beijing, China;Key Lab of Intell. Info. Process, Inst. of Comput. Tech., Chinese Academy of Sciences, China, Beijing 100080, China, Beijing, China;National Engineering Laboratory for Video Technology (NELVT), School of EE & CS, Peking University, Beijing 100871, China, Beijing, China;National Engineering Laboratory for Video Technology (NELVT), School of EE & CS, Peking University, Beijing 100871, China, Beijing, China;National Engineering Laboratory for Video Technology (NELVT), School of EE & CS, Peking University, Beijing 100871, China, Beijing, China;National Engineering Laboratory for Video Technology (NELVT), School of EE & CS, Peking University, Beijing 100871, China, Beijing, China
Venue:
Proceedings of the international conference on Multimedia
Year:
2010

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Abstract

Visual saliency can be a useful tool for image content analysis such as automatic image cropping and image compression. In existing methods on visual saliency detection, most of them are related to the model of receptive field. In this paper, we propose a bottom-up model which introduces 2D Log-Gabor wavelets for saliency detection. Compared with the traditional model of receptive field, the 2D Log-Gabor wavelets can better simulate the biological characteristics of the simple cortical cell in the receptive filed. Moreover, we also incorporate the influence of center bias into our model, which is a common phenomenon that directs visual attention to the center of images in natural scenes. Experimental results show that our approach outperforms three state-of-the-art approaches remarkably.