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Active and Attentive LADAR Scanning for Automatic TargetRecognition

机译:主动和专心LADAR扫描可自动识别目标

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In this work we examine the dynamic implications of active and attentive scanning for LADAR based automatic target/object recognition and show that a dynamically constrained, scanner based, ATR system's ability to identify objects in real-time is improved through attentive scanning. By actively and attentively scanning only salient regions of an image at the density required for recognition, the amount of time it takes to find a target object in a random scene is reduced. A LADAR scanner's attention is guided by identifying areas-of-interest using a visual saliency algorithm on electro-optical images of a scene to be scanned. Identified areas-of-interest are inspected in order of decreasing saliency by scanning the most salient area and saccading to the next most salient area until the object-of-interest is recognized. No ATR algorithms are used; instead, an object is considered to be recognized when a threshold density of pixels-on-target is reached.
机译:在这项工作中,我们研究了主动和专心扫描对基于LADAR的自动目标/物体识别的动态含义,并表明通过专心扫描提高了动态受限,基于扫描仪的ATR系统实时识别物体的能力。通过以识别所需的密度主动和专注地扫描图像的显着区域,可以减少在随机场景中找到目标物体所花费的时间。通过使用视觉显着性算法在要扫描的场景的电光图像上识别出感兴趣的区域,可以引导LADAR扫描仪的注意力。通过扫描最显着的区域并移动到下一个最显着的区域,直到识别出感兴趣的对象为止,以降低显着性的顺序检查已识别的感兴趣区域。没有使用ATR算法;相反,当达到目标像素的阈值密度时,就认为物体被识别。

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