光学学报, 2017, 37 (3): 0318012, 网络出版: 2017-03-08   

一种监控视频人脸图像超分辨技术 下载: 692次

A Super Resolution Technology of Face Image for Surveillance Video
王嫣然 1,2,*罗宇豪 1,2尹东 1,2
作者单位
1 中国科学技术大学信息科学技术学院, 安徽 合肥 230027
2 中国科学院电磁空间信息重点实验室, 安徽 合肥 230027
摘要
由于目前监控视频所拍摄的人脸图像目标较小、难以辨识, 图像超分辨处理已成为亟待解决监控视频图像实际应用问题的技术和手段。提出了一种针对室外监控视频人脸图像的超分辨技术,利用先验知识设置图像训练集, 并进行图像空间转化、去噪等预处理操作; 设计八层卷积神经网络并对各层类型及连接方式进行设定, 同时设定激活函数类型及各层间传递方式函数; 初始化参数并根据训练集训练网络; 根据损失函数反向调整卷积核和偏置参数, 完成图像输出。经过大量实际监控视频图像测试, 并将本文方法和现有其他方法做对比, 实验结果表明,本文方法在图像超分辨效果和处理速度上均有一定的优势。
Abstract
Face targets in image taken by the current surveillance video are small and difficult to identify. The image super resolution processing has become the technology and means to solve the image practical application problems of surveillance video. A super resolution technology for outdoor surveillance video face image is proposed. The prior knowledge is used to construct the image training set, and some pre-processing operations like the image space conversion and denoising are operated. The convolutional neural network with eight layers is designed, and its layer types and connection mode are set. Meanwhile, the activation function types and the transmission mode functions among layers are set. The network parameters are initialized and the network is trained according to the training set. The convolution kernels and bias parameters are adjusted reversely by the loss function, and the image output is implemented. Through a large number of actual monitoring video image tests, and compared with other existing methods, the experimental results show that the proposed method has certain advantages in the effect of image super resolution and processing speed.

王嫣然, 罗宇豪, 尹东. 一种监控视频人脸图像超分辨技术[J]. 光学学报, 2017, 37(3): 0318012. Wang Yanran, Luo Yuhao, Yin Dong. A Super Resolution Technology of Face Image for Surveillance Video[J]. Acta Optica Sinica, 2017, 37(3): 0318012.

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