基于空间复用和叠加成像的目标检测与跟踪

Shaoyi Li, Minzhou Dong, Kai Zhang, Jie Yan
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引用次数: 0

摘要

针对监控应用中大视场连续目标检测与跟踪的问题,提出了一种基于空间复用和叠加成像技术的大视场目标检测与跟踪新方法。该系统采用球面透镜阵列和具有宽视场和压缩采样特性的共焦平面结构。重点研究了基于叠加成像的运动目标检测方法。该方法将每个像素建模为高斯混合模型,同时评估高斯分布以确定哪一个最可能来自背景过程。因此,背景和前景是分开的。研究了运动目标的解码和跟踪方法,即根据叠加空间中的位置和速度准则对目标拷贝进行分类,得到目标位置的解码集。最后,对目标检测和解码算法进行了仿真,结果表明该方法可以在大视场范围内进行目标检测和跟踪。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Target detection and tracking based on spatially multiplexed and superposition imaging
Addressing continuous target detection and tracking over a large field of view in surveillance application, a novel method to detect and track target is presented in a wide field of view based on spatially multiplexed and superposition imaging technique. This system architecture is proposed by using the spherical lens array and confocal plane with the character of wide field and compressive sampling. And the method of moving target detection with superposition imaging is studied emphatically. This method models each pixel as a Gaussian mixture model, while the Gaussian distributions are evaluated to determine which are most likely to result from a background process. Accordingly the background and foreground are separated. Also, the method of moving target decoding and tracking is researched, which means that target location is decoded based on a set resulting from classifying target copies according to position and velocity criteria in the superposition space. Finally, the target detection and decoding algorithm are simulated and the results show that this method can perform target detection and tracking over a wide field of view.
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