| 基于视觉注意机制的交通标志检测 |
| |
| 引用本文： | 刘芳,邹琪.基于视觉注意机制的交通标志检测[J].计算机工程,2013,39(2):192-196. |
| |
| 作者姓名： | 刘芳 邹琪 |
| |
| 作者单位： | 北京交通大学计算机与信息技术学院,北京,100044 |
| |
| 基金项目： | 国家自然科学基金资助项目(60902058)；北京市自然科学基金资助项目(4112047)；中央高校基本科研业务费专项基金资助项目(2012JBM026) |
| |
| 摘 要： | 根据人类视觉感知理论，将自底向上和自顶向下的注意机制相结合，融入到交通标志检测中，提出一种基于视觉注意机制的交通标志检测方法。根据2种注意模型提取颜色、形状、亮度等多种特征，生成显著图，利用WTA网络找到感兴趣区域，即交通标志区域。实验结果表明，该方法能在复杂背景图像中准确定位交通标志。
|
| 关 键 词： | 注意机制 显著图 边缘检测 感兴趣区域 特征提取 |
| 收稿时间： | 2012-05-20 |
| 修稿时间： | 2012-07-17 |
Traffic Sign Detection Based on Visual Attention Mechanism |
| |
| LIU Fang
,
ZOU Qi.Traffic Sign Detection Based on Visual Attention Mechanism[J].Computer Engineering,2013,39(2):192-196. |
| |
| Authors: | LIU Fang ZOU Qi |
| |
| Affiliation: | (School of Computer and Information Technology, Beijing Jiaotong University, Beijing 100044, China) |
| |
| Abstract: | Two models of visual attention, bottom-up and top-down, which are consistent with human visual perception are introduced to traffic sign detection region. In this paper, it puts forward a way of traffic sign detection based on the visual saliency map. The features of color, shape, intensity and orientation are obtained to make saliency map. It finds the Region of Interest(ROI) by using of the Winners Take All(WTA) network. Experimental results show this method can accurately position the traffic sign in the cases of complex background images. |
| |
| Keywords: | attention mechanism saliency map edge detection Region of Interest(ROI) feature extraction |
| 本文献已被 CNKI 万方数据 等数据库收录！ |
| 点击此处可从《计算机工程》浏览原始摘要信息 |
|
点击此处可从《计算机工程》下载全文 |
