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CART III: Improved camouflage assessment using moving target indication

机译:CART III:使用移动目标指示改进迷彩评估

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In order to facilitate systematic, computer aided improvements of camouflage and concealment assessment methods, the software system CART (Camouflage Assessment in Real-Time) was built up for the camouflage assessment of objects in image sequences (see contributions to SPIE 2007 and SPIE 2008 [1], [2]). It works with visual-optical, infrared and SAR image sequences. The system comprises a semi-automatic annotation functionality for marking target objects (ground truth generation) including a propagation of those markings over the image sequence for static as well as moving scene objects, where the recording camera may be static or moving. The marked image regions are evaluated by applying user-defined feature extractors, which can easily be defined and integrated into the system via a generic software interface.rnThis article presents further systematic enhancements made in the recent year and addresses particularly the task of the detection of moving vehicles by latest image exploitation methods for objective camouflage assessment in these cases. As a main topic, the loop was closed between the two natural opposites of reconnaissance and camouflage, which was realized by incorporating ATD (Automatic Target Detection) algorithms into the computer aided camouflage assessment. Since object (and sensor) movement is an important feature for many applications, different image-based MTI (Moving Target Indication) algorithms were included in the CART system, which rely on changes in the image plane from an image to the successive one (after camera movements are automatically compensated). Additionally, the MTI outputs over time are combined in a certain way which we call "snail track" algorithm. The results show that their output provides a valuable measurement for the conspicuity of moving objects and therefore is an ideal component in the camouflage assessment. It is shown that image-based MTI improvements lead to improvements in the camouflage assessment process.
机译:为了促进系统的,计算机辅助的伪装和隐蔽评估方法的改进,建立了CART(实时伪装评估)软件系统,用于对图像序列中的对象进行伪装评估(请参阅SPIE 2007和SPIE 2008的贡献[ 1],[2])。它适用于视觉光学,红外和SAR图像序列。该系统包括用于标记目标对象(地面真相生成)的半自动注释功能,包括在静态和移动场景对象(记录相机可能是静态或移动的)的图像序列上传播这些标记。标记的图像区域通过应用用户定义的特征提取器进行评估,这些特征提取器可以通过通用软件界面轻松定义并集成到系统中。本文介绍了近年来的进一步系统增强,尤其是针对图像检测的任务。在这种情况下,通过最新的图像开发方法对移动的车辆进行客观伪装评估。作为一个主要主题,侦查和迷彩的两个自然对立之间是闭合的,这是通过将ATD(自动目标检测)算法整合到计算机辅助迷彩评估中来实现的。由于对象(和传感器)移动是许多应用程序的重要功能,因此CART系统中包括了不同的基于图像的MTI(移动目标指示)算法,该算法依赖于图像平面从图像到连续图像的变化。相机的运动会自动补偿)。此外,随着时间的推移,MTI输出将以某种我们称为“蜗牛跟踪”算法的方式进行组合。结果表明,它们的输出为运动物体的醒目提供了有价值的度量,因此是伪装评估中的理想组件。结果表明,基于图像的MTI改进导致伪装评估过程的改进。

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