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Camouflage assessment considering human perception data

机译:考虑人类感知数据的伪装评估

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Shape and shape disruption have significant influence to the human target acquisition mechanism. A special testing method (the so called `photo-simulation') was developed in the eighties to present a set of image slides of camouflaged and not camouflaged objects in preferably natural backgrounds to military personnel to quantify differences in object camouflage effectiveness. Statistically significant results were achieved, however, the high test requirements limited its practical use. The project is motivated by an urgent need for a camouflage evaluation system based on computer vision with a fast response so that the user in a field test can be supported to further improve his camouflage skills. Hence, the photo simulation method cannot be regarded as obsolete, it can be used to compare the results of the camouflage evaluation system with the results of human perception. With an human-in-the-loop computer based camouflage assessment system, processing should be sped up by some orders of magnitude, could be automated for field tests and would yield several additional features. To overcome the problem of quantifying e.g. texture similarity of different camouflage nets to blend into the natural background, an image processing/visualization method was pursued by the Austrian Ministry of Defense. Now the same image-sets can be used for the human photo-simulation as well as for segmentation/classification by the camouflage assessment tool. Today a modified Euclid-distance measurement for visual images is being used while similarity of shapes (gestalt) to a selected region can be visualized. Feature selection is being done by training a neural network with the results of the human perception data. A cost effective prototype of a camouflage assessment tool based on standard hardware can be presented. Its promising performance gives hope to get beyond subjective camouflage experts stimuli. In the next project phase also thermal images shall be handled with the camouflage assessment tool.
机译:形状和形状破坏对人类目标采集机制具有显着影响。在八十年代开发了一种特殊的测试方法(所谓的“照片仿真”)以呈现伪装的一组图像幻灯片,而不是优选地在军事人员中的自然背景中的伪装物体,以量化伪装效率的差异。实现了统计上显着的结果,然而,高测试要求限制了其实际使用。该项目通过迫切需要基于计算机视觉的伪装评估系统,其具有快速响应,以便可以支持现场测试中的用户进一步提高他的伪装技能。因此,光仿真方法不能被视为已过时,可用于将伪装评估系统的结果与人类感知结果进行比较。通过基于LOOP计算机的迷彩评估系统,应通过一些数量级来加工处理,可以自动用于现场测试,并产生几种附加功能。克服量化的问题。奥地利国防部追求不同伪装网融入自然背景中的纹理相似性,图像处理/可视化方法。现在,相同的图像集可用于人类照片仿真以及伪装评估工具的分段/分类。如今,正在使用用于视觉图像的改进的欧几里特距离测量,而可以可视化对所选区域的形状(GeStalt)的相似性。通过培训具有人类感知数据的结果的神经网络来完成特征选择。可以提出基于标准硬件的伪装评估工具的成本有效的原型。其有希望的表现使得希望超越主观伪装专家刺激。在下一个项目阶段,也应使用迷彩评估工具处理热图像。

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