Plane Extraction(平面提取)研究综述
Plane Extraction 平面提取 - In the proposed approach, a random sample consensus (RANSAC)-based plane fitting technique was utilized for plane extraction, and cross-feature points were extracted from the polar view transform of segmented planes. [1] In this paper, a novel method for point cloud segmentation based on Euclidean clustering and multi-plane extraction is proposed. [2] Our algorithm, developed in C++, is based on plane extraction by means of the RANSAC algorithm followed by the minimization of the quadrate sum of points-plane distance. [3] , RGBD, LiDAR) configuration, in which the camera is used for point feature tracking and depth sensor for plane extraction. [4] Recently, an image encryption scheme combining bit-plane extraction with multiple chaotic maps (IESBC) was proposed. [5] Whether it is object detection, model reconstruction, laser odometry, or point cloud registration: Plane extraction is a vital component of many robotic systems. [6]在所提出的方法中，基于随机样本一致性（RANSAC）的平面拟合技术用于平面提取，并从分割平面的极视图变换中提取交叉特征点。 [1] 本文提出了一种基于欧几里得聚类和多平面提取的点云分割新方法。 [2] 我们的算法是用 C++ 开发的，它是基于通过 RANSAC 算法提取平面，然后最小化点-平面距离的平方和。 [3] , RGBD, LiDAR) 配置，其中相机用于点特征跟踪和深度传感器用于平面提取。 [4] 最近，提出了一种将位平面提取与多混沌映射（IESBC）相结合的图像加密方案。 [5] 无论是对象检测、模型重建、激光里程计还是点云配准：平面提取是许多机器人系统的重要组成部分。 [6]
plane extraction method 平面提取法
We have used a cubic-logistic map, Discrete Wavelet Transform (DWT), and bit-plane extraction method to encrypt the medical images at the bit-level rather than pixel-level. [1] Therefore, in this paper, we propose a voxel-grid-center-constrained iterative adaptive plane extraction method that can meet the speedability without losing the accuracy of the detected planes. [2] PlaneRCNN makes an important step towards robust plane extraction method, which would have immediate impact on a wide range of applications including Robotics, Augmented Reality, and Virtual Reality. [3] This paper presents a simple yet powerful rotational-guided optimal cutting-plane extraction method which can provide an effective way for skeleton extraction, simplification, surface reconstruction and boundary extraction. [4]我们使用三次逻辑图、离散小波变换 (DWT) 和位平面提取方法在位级而不是像素级对医学图像进行加密。 [1] 因此，在本文中，我们提出了一种体素网格中心约束的迭代自适应平面提取方法，该方法可以在不损失检测平面精度的情况下满足速度要求。 [2] PlaneRCNN 朝着稳健的平面提取方法迈出了重要的一步，这将对包括机器人、增强现实和虚拟现实在内的广泛应用产生直接影响。 [3] 本文提出了一种简单而强大的旋转引导最优切割平面提取方法，为骨架提取、简化、曲面重建和边界提取提供了一种有效的方法。 [4]