计算机科学
迭代最近点
目标检测
人工智能
算法
点(几何)
级联
迭代法
模式识别(心理学)
计算机视觉
点云
数学
几何学
色谱法
化学
作者
Anastasia Kober,Alexey Ruchay,Konstantin Dorofeev
摘要
In this paper, we propose an algorithm for the detection of local features in depth maps. The local features can be utilized for determination of special points for Iterative Closest Point (ICP) algorithms. The proposed algorithm employs a novel approach based a cascade mechanism, which can be applied for several 3D keypoint detection algorithms. Computer simulation and experimental results obtained with the proposed algorithm in real-life scenes are presented and compared with those obtained with state-of-the-art algorithms in terms of detection efficiency, accuracy, and speed of processing. The results show an improvement in the accuracy of 3D object reconstruction using the proposed algorithm followed by ICP algorithms.
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