title: The study of randomized visual saliency detection algorithm.
abstract: Image segmentation process for high quality visual saliency map is very dependent on the existing visual saliency metrics. It is mostly only get sketchy effect of saliency map, and roughly based visual saliency map will affect the image segmentation results. The paper had presented the randomized visual saliency detection algorithm. The randomized visual saliency detection method can quickly generate the same size as the original input image and detailed results of the saliency map. The randomized saliency detection method can be applied to real-time requirements for image content-based scaling saliency results map. The randomization method for fast randomized video saliency area detection, the algorithm only requires a small amount of memory space can be detected detailed oriented visual saliency map, the presented results are shown that the method of visual saliency map used in image after the segmentation process can be an ideal segmentation results.
authors.affiliation: School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing 210094, China ; School of Computer and Communication Engineering, Changsha University of Science and Technology, Changsha 410114, China.
authors.forename: Yuantao
authors.initials: Y
authors.lastname: Chen
authors.affiliation: School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing 210094, China ; School of Computer and Communication Engineering, Changsha University of Science and Technology, Changsha 410114, China.
authors.forename: Weihong
authors.initials: W
authors.lastname: Xu
authors.affiliation: School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing 210094, China ; Department of Computer Science and Technology, Hunan Vocational Institute of Safety & Technology, Changsha 410151, China.
authors.forename: Fangjun
authors.initials: F
authors.lastname: Kuang
authors.affiliation: School of Computer Science and Engineering, Nanjing University of Science and Technology, Nanjing 210094, China.
authors.forename: Shangbing
authors.initials: S
authors.lastname: Gao
mesh_terms: D000465:Algorithms; D000818:Animals; D001185:Artificial Intelligence; D001288:Attention; D003196:Computer Graphics; D003198:Computer Simulation; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008962:Models, Theoretical; D010363:Pattern Recognition, Automated; D011897:Random Allocation; D012984:Software