Multiple View Point Cloud Registration Based on 3D Lines
نویسندگان
چکیده
A point cloud registration method based on 3D lines extraction from 3D data to register point cloud with obvious edges is proposed in this paper. Firstly, the line feature point cloud (LFPC), which is corresponding to the objects' edges, is extracted from the measured 3D data by using surface curvature as a measure. Then, through applying the 3D Hough transformation on LFPC, the line directions and positions are extracted respectively. Thus, the 3D lines corresponding to the edges in the two point clouds to be registered are obtained. Finally, a 3D lines matching and registration algorithm is proposed to accomplish the registration. Furthermore, the experiment is conducted to testify the feasibility of proposed method. The contribution of this paper is to propose a novel 3D Hough based lines extraction algorithm as well as a novel 3D line matching and registration algorithm, which can also be used in other 3D point cloud processing.
منابع مشابه
Automatic Registration of Laser Scanned Color Point Clouds Based on Common Feature Extraction
Point cloud data acquisition with laser scanners provides an effective way for 3D as-built modeling of a construction site. Due to the limited view of a scan, multiple scans are required to cover the whole scene, and a registration process is needed to merge them together. The aim of this paper is to introduce a novel method that automatically registers colored 3D point cloud sets without using...
متن کاملRegistration of Partial 3D Point Clouds Acquired from a Multi-view Camera for Indoor Scene Reconstruction
In this paper, a novel projection-based method is presented to register partial 3D point clouds, acquired from a multi-view camera, for 3D reconstruction of an indoor scene. In general, conventional registration methods for partial 3D point clouds require a high computational complexity and much time for registration. Moreover, these methods are not robust for 3D point cloud which has a low pre...
متن کاملA novel Local feature descriptor using the Mercator projection for 3D object recognition
Point cloud processing is a rapidly growing research area of computer vision. Introducing of cheap range sensors has made a great interest in the point cloud processing and 3D object recognition. 3D object recognition methods can be divided into two categories: global and local feature-based methods. Global features describe the entire model shape whereas local features encode the neighborhood ...
متن کاملAutomatic Object Recognition and Registration of Dynamic Construction Equipment from a 3d Point Cloud
This paper introduces a model-based automatic object recognition and registration framework to assist heavy equipment operators in rapidly perceiving 3D working environment at dynamic construction sites. A video camera and a laser scanner were utilized in this study to rapidly recognize and register dynamic target objects in a 3D space by dynamically separating target object’s point cloud data ...
متن کاملSimultaneous registration of multi-view range images with adaptive kernel density estimation
3D surface registration can be considered one of the crucial stages of reconstructing 3D objects from depth sensor data. Aligning pairs of surfaces is a well studied problem that has resulted in fast and usually reliable algorithms addressing the task. The generalised problem of globally aligning multiple surfaces is a more complex task that has received less attention yet remains a fundamental...
متن کامل