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Non-Cooperative Persons Identification at a Distance with 3D Face Modeling

机译:非合作人员​​识别3D面部建模的距离

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We present an approach to identify non-cooperative individuals at a distance from a sequence of images using 3D face models. Most biometric features (such as fingerprints, hand shape, iris or retinal scans) require cooperative subjects in close proximity to the biometric system. We process images acquired with an ultra-high resolution video camera, infer the location of the subjects'' head, use this information to crop the region of interest, build a 3D face model, and use this 3D model to perform biometric identification. To build the 3D model, we use an image sequence, as natural head and body motion provides enough viewpoint variation to perform stereo-motion for 3D face reconstruction. Experiments using a 3D matching engine suggest the feasibility of proposed approach for recognition against 3D galleries.
机译:我们提出了一种方法来识别非协作个体在使用3D面部模型的图像序列的距离处。大多数生物识别特征(如指纹,手形,虹膜或视网膜扫描)都需要与生物识别系统附近的协作受试者。我们处理使用超高分辨率摄像机获取的图像,推断对象的头部的位置,使用这些信息来裁剪感兴趣的区域,构建3D面部模型,并使用该3D模型执行生物识别识别。为了构建3D模型,我们使用图像序列,因为自然头部和身体运动提供足够的视点变化以对3D面重建执行立体运动。使用3D匹配发动机的实验表明了建议识别3D画廊的方法的可行性。

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