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Real-Time EO/IR Sensor Fusion on a Portable Computer and Head Mounted Display

机译:便携式计算机和头戴式显示器上的实时EO / IR传感器融合

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摘要

Multi-sensor platforms are widely used in surveillance video systems for both military and civilian applications. The complimentary nature of different types of sensors (e.g. EO and IR sensors) makes it possible to observe the scene under almost any condition (dayight/fog/smoke). In this paper, we propose an innovative EO/IR sensor registration and fusion algorithm which runs real-time on a portable computing unit with head-mounted display. The EO/IR sensor suite is mounted on a helmet for a dismounted soldier and the fused scene is shown in the goggle display upon the processing on a portable computing unit. The linear homography transformation between images from the two sensors is pre-computed for the mid-to-far scene, which reduces the computational cost for the online calibration of the sensors. The system is implemented in a highly optimized C++ code, with MMX/SSE, and performing a real-time registration. The experimental results on real captured video show the system works very well both in speed and in performance.
机译:多传感器平台广泛用于军事和民用应用的监视视频系统。不同类型的传感器(例如EO和IR传感器)具有互补性,因此可以在几乎任何条件下(白天/夜晚/雾/烟)观察场景。在本文中,我们提出了一种创新的EO / IR传感器配准和融合算法,该算法在带有头戴式显示器的便携式计算单元上实时运行。 EO / IR传感器套件安装在头盔上,供下岗士兵使用,在便携式计算机上进行处理后,护目镜显示融合的场景。来自两个传感器的图像之间的线性单应变换针对中远景进行了预先计算,这减少了传感器在线校准的计算成本。该系统使用高度优化的C ++代码,MMX / SSE来实现,并执行实时注册。在实际捕获的视频上的实验结果表明,该系统在速度和性能上都运行良好。

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