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ToF Depth Image Motion Blur Detection Using 3D Blur Shape Models

机译:使用3D模糊形状模型的ToF深度图像运动模糊检测

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Time-of-flight cameras produce 3D geometry enabling faster and easier 3D scene capturing. The depth camera, however, suffers from motion blurs when the movement from either camera or scene appears. Unlike other noises, depth motion blur is hard to eliminate by any general filtering methods and yields the serious distortion in 3D reconstruction, typically causing uneven object boundaries and blurs. In this paper, we provide a through analysis on the ToF depth motion blur and a modeling method which is used to detect a motion blur region from a depth image. We show that the proposed method correctly detects blur regions using the set of all possible motion artifact models.
机译:飞行时间相机产生3D几何图形,可以更快,更轻松地捕获3D场景。但是,当出现来自相机或场景的运动时,深度相机会遭受运动模糊的困扰。与其他噪声不同,深度运动模糊很难通过任何常规的滤波方法消除,并且会在3D重建中产生严重的失真,通常会导致不均匀的对象边界和模糊。在本文中,我们提供了对ToF深度运动模糊的透彻分析和一种用于从深度图像中检测运动模糊区域的建模方法。我们表明,所提出的方法使用所有可能的运动伪影模型集来正确检测模糊区域。

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