公共区域监控视频数据目标特征跟踪定位方法

为了提高公共区域监控视频的目标定位检测能力,需要进行目标特征跟踪定位算法设计,提出一种基于图像超分辨率重建的公共区域监控视频数据目标特征跟踪定位方法。构建公共区域监控视频的三维图像重建模型,采用边缘层的高分辨融合方法进行公共区域监控视频图像数据的三维结构重组,提取公共区域监控视频的关键特征点,用图像退化模型进行公共区域监控视频数据目标特征检测,结合线性滤波模型使得监测输出图像满足最优匹配特征解,提高对公共区域监控视频数据目标特征跟踪能力。引入引导滤波方法进行公共区域监控视频数据的图像超分辨重建,实现对目标特征准确跟踪定位。仿真结果表明,采用该方法进行公共区域监控视频数据目标特征跟踪定位的准确性较高,图像重建能力较强,归一化均方根误差较小。

Target tracking and location method for common area surveillance video data

In order to improve the ability of target location detection in public area surveillance video,it is necessary to design a target feature tracking and localization algorithm.A new method of target tracking and localization based on image super-resolution reconstruction is proposed.The 3 D image reconstruction model of common area surveillance video is constructed.The high resolution fusion method of edge layer is used to reconstruct the 3 D structure of public area surveillance video image data,and the key feature points of public area surveillance video are extracted.The image degradation model is used to monitor the target features of common area surveillance video data,and the linear filtering model is used to make the monitoring output image satisfy the optimal matching feature solution,which improves the ability of feature tracking for common area surveillance video data.A guided filtering method is introduced for super-resolution reconstruction of video data in common area surveillance to accurately track and locate the target features.The simulation results show that the proposed method has high accuracy,strong ability of image reconstruction and less error of normalized root mean square(RMS).