| 崔少华,汪徐德,王江涛,单 巍.高斯建模和卷积神经网络联合的红外视频行人检测方法[J].电子测量与仪器学报,2020,34(5):140-148 |
| 高斯建模和卷积神经网络联合的红外视频行人检测方法 |
| Infrared video pedestrian detection method via Gauss modeling and convolutional neural network |
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| DOI： |
| 中文关键词: 红外视频 图像处理 混合高斯模型 LeNet-7 系统 检测率 |
| 英文关键词:infrared video image processing Gauss mixture model LeNet-7 system detection rate |
| 基金项目:国家自然科学基金(11504121)、安徽省教育厅项目 (2017kfk044,2018jyxm0530,201910373104)资助 |
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| 中文摘要: |
| 针对传统红外视频中存在行人互相遮挡导致无法提取前景目标、检测率较低等问题,提出了高斯背景建模和卷积神经
网络联合的红外视频行人检测方法。 首先,对于连续序列红外图像,通过混合高斯模型提取前景目标;然后,对于行人互相遮挡
的前景目标,以亮度曲线图中的谷底为分割点,通过方向投影分离出单行人目标区域;最后,将确定的感兴趣区域输入训练好的
LeNet-7 系统。 3 个不同测试集的检测实验表明,该方法具有良好的检测效果,与传统方法相比,该算法的检测率达到 99%以
上,虚警率低至 0%。 |
| 英文摘要: |
| A joint infrared video pedestrian method is proposed based on Gauss background modeling and convolution neural network, to
address the problems of inability to extract foreground targets and low detection rate in traditional method. Firstly, for continuous
sequence infrared images, the foreground targets are extracted by the mixture Gaussian model. Then, for the foreground targets which are
occluded by pedestrians, the valley bottom of the luminance curve is used as the segmentation point. While, the single pedestrian target
area is separated by directional projection. Finally, the determined region of interest is input into the trained LeNet-7 system.
Experiments on three different test sets demonstrate that the proposed method has good detection effect. Compared with the traditional
method, the detection rate of the proposed method is over 99%, and the false alarm rate is as low as 0%. |
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