Geometric 3D point cloud compression

نویسندگان

  • Vicente Morell
  • Sergio Orts
  • Miguel Cazorla
  • José García Rodríguez
چکیده

This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain. ARTICLE INFO ABSTRACT Article history: The use of 3D data in mobile robotics applications provides valuable information about the robot's environment but usually the huge amount of 3D information is unmanageable by the robot storage and computing capabilities. A data compression is necessary to store and manage this information but preserving as much information as possible. In this paper, we propose a 3D lossy compression system based on plane extraction which represent the points of each scene plane as a Delaunay triangulation and a set of points/area information. The compression system can be customized to achieve different data compression or accuracy ratios. It also supports a color segmentation stage to preserve original scene color information and provides a realistic scene reconstruction. The design of the method provides a fast scene reconstruction useful for further visualization or processing tasks.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Target detection Bridge Modelling using Point Cloud Segmentation Obtained from Photogrameric UAV

In recent years, great efforts have been made to generate 3D models of urban structures in photogrammetry and remote sensing. 3D reconstruction of the bridge, as one of the most important urban structures in transportation systems, has been neglected because of its geometric and structural complexity. Due to the UAV technology development in spatial data acquisition, in this study, the point cl...

متن کامل

A 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 کامل

Detection of some Tree Species from Terrestrial Laser Scanner Point Cloud Data Using Support-vector Machine and Nearest Neighborhood Algorithms

acquisition field reference data using conventional methods due to limited and time-consuming data from a single tree in recent years, to generate reference data for forest studies using terrestrial laser scanner data, aerial laser scanner data, radar and Optics has become commonplace, and complete, accurate 3D data from a single tree or reference trees can be recorded. The detection and identi...

متن کامل

Geometric Primitive Extraction for 3D Model Reconstruction

3D map building is a complex robotics task which needs mathematical robust models. From a 3D point cloud, we can use the normal vectors to these points to do feature extraction. In this paper, we propose to extract geometric primitives (e.g. planes) from the cloud. We will present a robust method for normal estimation.

متن کامل

A novel method for locating the local terrestrial laser scans in a global aerial point cloud

In addition to the heterogeneity of aerial and terrestrial views, the small scale terrestrial point clouds are hardly comparable with large scale and overhead aerial point clouds. A hierarchical method is proposed for automatic locating of terrestrial scans in aerial point cloud. The proposed method begins with detecting the candidate positions for the deployment of the terrestrial laser scanne...

متن کامل

Conditional Random Fields for Airborne Lidar Point Cloud Classification in Urban Area

Over the past decades, urban growth has been known as a worldwide phenomenon that includes widening process and expanding pattern. While the cities are changing rapidly, their quantitative analysis as well as decision making in urban planning can benefit from two-dimensional (2D) and three-dimensional (3D) digital models. The recent developments in imaging and non-imaging sensor technologies, s...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:
  • Pattern Recognition Letters

دوره 50  شماره 

صفحات  -

تاریخ انتشار 2014