Visual Saliency Based on Local and Global Features in the Spatial Domain
The human visual system can quickly and efficiently capture the salient objects in a scene. Based on the biological mechanism, a new multi-scale saliency analysis method is proposed in this paper, in which the differences of region colors and spaces are calculated in different scale and their saliency map are fused together. First, we calculate the image saliency by using the color and space information of both local and global in single scale. Then by applying the multi-scale fusion, we can effectively inhibit outstanding but not salient region in each single scale, and different scale can also reflect salient region of the images from different aspects. The experiment results show that this algorithm can effectively predict the salient region attracting human attention. Our method has the state-of-the-art performance and achieves excellent results for salient objects of different sizes and salient region with complicated background in an image.
Keywords: local and global features , salient object detection£¬patch saliency£¬color and space difference£¬multi-scale fusing
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ABOUT THE AUTHORS
Chao Jia
Professor, PhD supervisor, born in 1967. In 1991, he received the B.E. degree in computer profession, Northeast Heavy Machinery Institute. In 1998, he received the M.Sc degree and in 2005 he received the Doctor degree in College of Information Science and Engineering, YanShan University, China. Since 2011 he has been with College of Information Science and Engineering as a Professor. Prof. He has published numerous papers, completed more than one large-scale project. Such as his main research interests include computer graphics, computer vision and image processing, virtual reality and virtual simulation.
Fang Hou
was born in 1987. She received the B.S. degree in College of Computer Science and Technology in Harbin Science and Technology University in 2011. Currently, she is a graduate student in College of Information Science and Engineering, Yanshan University, China. Her main research interests include computer vision and image processing.
Liangiang Duan
was born in 1985. He received the B.S. degree in College of Information Science and Engineering in Shandong Agricultural University in 2009. He received the M.Sc degree and in 2011. Currently, he is a doctor student in College of Information Science and Engineering, Yanshan University, China. His main research interests include computer vision and image processing.
Chao Jia
Professor, PhD supervisor, born in 1967. In 1991, he received the B.E. degree in computer profession, Northeast Heavy Machinery Institute. In 1998, he received the M.Sc degree and in 2005 he received the Doctor degree in College of Information Science and Engineering, YanShan University, China. Since 2011 he has been with College of Information Science and Engineering as a Professor. Prof. He has published numerous papers, completed more than one large-scale project. Such as his main research interests include computer graphics, computer vision and image processing, virtual reality and virtual simulation.
Fang Hou
was born in 1987. She received the B.S. degree in College of Computer Science and Technology in Harbin Science and Technology University in 2011. Currently, she is a graduate student in College of Information Science and Engineering, Yanshan University, China. Her main research interests include computer vision and image processing.
Liangiang Duan
was born in 1985. He received the B.S. degree in College of Information Science and Engineering in Shandong Agricultural University in 2009. He received the M.Sc degree and in 2011. Currently, he is a doctor student in College of Information Science and Engineering, Yanshan University, China. His main research interests include computer vision and image processing.
