Robust real-time 3D modeling of static scenes using solely a Time-of-Flight sensor

J. Feulner, J. Penne, E. Kollorz, J. Hornegger
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引用次数: 6

Abstract

An algorithm is proposed for the 3D modeling of static scenes solely based on the range and intensity data acquired by a time-of-flight camera during an arbitrary movement. No additional scene acquisition devices, like inertia sensor, positioning robots or intensity based cameras are incorporated. The current pose is estimated by maximizing the uncentered correlation coefficient between edges detected in the current and a preceding frame at a minimum frame rate of four fps and an average accuracy of 45 mm. The paper also describes several extensions for robust registration like multiresolution hierarchies and projection Iterative Closest Point algorithm. The basic registration algorithm and its extensions were intensively evaluated against ground truth data to validate the accuracy, robustness and real-time-capability.
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鲁棒的实时三维建模静态场景仅使用一个飞行时间传感器
提出了一种仅基于任意运动时飞行时间相机获取的距离和强度数据的静态场景三维建模算法。没有额外的场景采集设备,如惯性传感器,定位机器人或基于强度的相机。当前姿态通过最大化当前帧和前一帧检测到的边缘之间的无中心相关系数来估计,最小帧速率为4 fps,平均精度为45 mm。本文还介绍了鲁棒配准的几个扩展,如多分辨率层次和投影迭代最近点算法。针对地面真实数据对基本配准算法及其扩展进行了深入评估,以验证其准确性、鲁棒性和实时性。
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