@inproceedings{1816ba10ea1e4a7eb003af9661e9074e,
title = "Depth enhanced saliency detection method",
abstract = "Human vision system understands the environment from 3D perception. However, most existing saliency detection algorithms detect the salient foreground based on 2D image information. In this paper, we propose a saliency detection method using the additional depth information. In our method, saliency cues are provided to follow the laws of the visually salient stimuli in both color and depth spaces. Simultaneously, the 'center bias' is also extended to 'spatial' bias to represent the nature advantage in 3D image. In addition, We build a dataset to test our method and the experiments demonstrate that the depth information is useful for extracting the salient object from the complex scenes.",
keywords = "Depth map, RGB-D image, Saliency detection",
author = "Yupeng Cheng and Huazhu Fu and Xingxing Wei and Jiangjian Xiao and Xiaochun Cao",
year = "2014",
doi = "10.1145/2632856.2632866",
language = "英语",
isbn = "9781450328104",
series = "ACM International Conference Proceeding Series",
publisher = "Association for Computing Machinery ",
pages = "23--27",
booktitle = "ICIMCS 2014 - Proceedings of the 6th International Conference on Internet Multimedia Computing and Service",
address = "美国",
note = "6th International Conference on Internet Multimedia Computing and Service, ICIMCS 2014 ; Conference date: 10-07-2014 Through 12-07-2014",
}