Incremental and batch planar simplification of dense point cloud maps

نویسندگان
چکیده

برای دانلود باید عضویت طلایی داشته باشید

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

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Incremental and batch planar simplification of dense point cloud maps

Dense RGB-D SLAM techniques and high-fidelity LIDAR scanners are examples from an abundant set of systems capable of providing multi-million point datasets. These datasets quickly become difficult to process due to the sheer volume of data, typically containing significant redundant information, such as the representation of planar surfaces with millions of points. In order to exploit the richn...

متن کامل

Intrinsic point cloud simplification

Modelling and visualisation methods working directly with point-sampled geometry have developed into attractive alternatives to more traditional mesh-based surface processing. In this paper, we consider a vital step in any point-based surface processing pipeline, point cloud simplification. Building upon the intrinsic point cloud simplification idea put forward in [14], we obtain a simplificati...

متن کامل

Error-Controllable Simplification of Point Cloud

Point cloud simplification has become a vital step in any point-based surface processing pipeline. This paper describes a fast and effective algorithm for point cloud simplification with feature preservation. First, feature points are extracted by thresholding curvatures; Second, for non-feature points, they are covered by distinct balls, the points in each ball are substituted by an optimized ...

متن کامل

Comprehensive Analysis of Dense Point Cloud Filtering Algorithm for Eliminating Non-Ground Features

Point cloud and LiDAR Filtering is removing non-ground features from digital surface model (DSM) and reaching the bare earth and DTM extraction. Various methods have been proposed by different researchers to distinguish between ground and non- ground in points cloud and LiDAR data. Most fully automated methods have a common disadvantage, and they are only effective for a particular type of surf...

متن کامل

A new point cloud simplification algorithm

We present a new technique for the simplification of pointsampled geometry without any prior surface reconstruction. Using Fast Marching farthest point sampling for implicit surfaces and point clouds [1], we devise a coarse-tofine uniform or feature-sensitive simplification algorithm with user-controlled density guarantee. The algorithm is computationally and memory efficient, easy to implement...

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

ژورنال

عنوان ژورنال: Robotics and Autonomous Systems

سال: 2015

ISSN: 0921-8890

DOI: 10.1016/j.robot.2014.08.019