基于马尔可夫随机场的显著区域检测
Visual Salient Objects Detection Based on MRF
方静 1吴健 1崔志明1
作者信息
- 1. 苏州大学智能信息处理及应用研究所,江苏苏州215006
- 折叠
摘要
显著区域检测被应用在计算机视觉处理的各个方面，然而大目标和复杂背景中显著对象检测存在检测内容缺失和误检的问题。提出一种基于粗略显著区域的马尔可夫随机场（MRF）模型检测方法。首先，应用Harris角点检测定位粗略显著区域，去除边缘附近角点做凸包操作，然后基于粗略区域的先验概率，应用马尔可夫随机场模型检测图像显著区域。在图像测试库的实验结果显示．提出的检测方法提高了检测的准确度和完整度。
Abstract
Salieny detection is utilized in many vision tasks in recent years. But parts of objects missing and detect false are still big issue when the object of image is huge or the background is complex. In this paper, we propose a new computational saliency dectection model which is implemented with a coarse to fine strategy under MRF frame- work. Firstly, saliency points based on Harris are applied to get a coarse location of the saliency region. And then, based on the rough region, we compute a prior map for the MRF to achieve the final sailent objects detection. Experimental results on a dataset show that the detected section based on the model is more accurate and complete.
关键词
显著区域/目标检测/Harris角点/MRF/马尔可夫随机场Key words
saliency/object detection/Harris/MRF/Markov random field引用本文复制引用
基金项目
国家自然科学基金(60970015)
国家自然科学基金(61003054)
国家自然科学基金(61170020)
江苏省省级现代服务业(软件产业)发展专项引导资金项目([2009]332-64)
江苏省普通高校研究生科研创新计划项目(CXLX11_0072)
苏州大学科研预研基金()
出版年
2012
NETL
NSTL
维普
万方数据