scholarly journals High-Quality Contour Line Generation from LiDAR Point Clouds for the Area of Forests

2018 ◽  
Author(s):  
Zongyue Wang ◽  
Hongchao Ma ◽  
Cuiling Zheng ◽  
Rongxin Chen
Keyword(s):  
Break Line ◽  
Point Clouds ◽  
Shape Index ◽  
Contour Line ◽  
Threshold Method ◽  
Statistical Parameters ◽  
High Quality ◽  
Line Extraction ◽  
Contour Lines ◽  
Line Generation

A methodology for both accurate and smooth contour line generation from Light Detection and Ranging (LiDAR) point clouds is proposed in this paper. In order to improve the accuracy of contour lines in the area of forests, constrained triangulation networks with break lines are then constructed to generate contour lines. In break line extraction, a bi-threshold method for edge line detection is used to extract both complete and reliable break lines. A point clouds elevation adjustment with constrain of break lines and an interpolator considering a contour interval is proposed to improve the smoothness of contour lines. The proposed interpotator is also can avoid contour line intersection when contour lines are interpolated. Statistical parameters and shape index are then used to evaluate quantitatively the accuracy and smoothness of the resultant contour lines, which fill in the blank of contour lines evaluation in theory. The experiments show that high-quality contours in terms of smoothness and accuracy can be generated from LiDAR point clouds.

scholarly journals DEFINITION OF CONTOUR LINES INTERPOLATION OPTIMAL METHODS FOR E-GOVERNMENT SOLUTIONS

2018 ◽  
Vol IV-4 ◽  
pp. 163-170
Author(s):  
A. Noskov ◽  
A. Zipf
Keyword(s):  
Visual Analysis ◽  
Optimal Algorithm ◽  
Contour Line ◽  
Optimal Interpolation ◽  
Data Sets ◽  
High Quality ◽  
Simple Method ◽  
Contour Lines ◽  
Important Challenge

<p><strong>Abstract.</strong> Citizens expect high quality and rich e-Government solutions. Map based applications could be significantly improved by utilization of digital elevation models (DEMs). DEMs can be produced using expensive modern remote sensing solutions (e.g., LIDAR). Such data are not available for the wide public. Thus, it is very effective to use contour line maps to derive high-quality DEMs. For many cities around the world, contour line maps available under liberal licenses. Defining an optimal algorithm of contour line interpolation and evaluation of the quality of DEM is an important challenge. In this article, we propose a simple method allowing users to evaluate the quality of DEM produced from a contour line map and define an optimal interpolation algorithm. This method was tested on Turin (Italy) data sets. The results were proved by a visual analysis. The approach is utilized in existing e-Government WebGIS services. This work introduces an information theory-based approach to DEM quality assessment. The results can be utilized in various domains related to DEM quality assurance.</p>

scholarly journals ANALYSIS OF 3D BUILDING MODELS ACCURACY BASED ON THE AIRBORNE LASER SCANNING POINT CLOUDS

2018 ◽  
Vol XLII-2 ◽  
pp. 797-804 ◽  
Author(s):  
W. Ostrowski ◽  
M. Pilarska ◽  
J. Charyton ◽  
K. Bakuła
Keyword(s):  
Point Cloud ◽  
Laser Scanning ◽  
Large Scale ◽  
Point Clouds ◽  
3D Models ◽  
Airborne Laser Scanning ◽  
Aerial Images ◽  
Statistical Parameters ◽  
Airborne Laser ◽  
Building Models

Creating 3D building models in large scale is becoming more popular and finds many applications. Nowadays, a wide term “3D building models” can be applied to several types of products: well-known CityGML solid models (available on few Levels of Detail), which are mainly generated from Airborne Laser Scanning (ALS) data, as well as 3D mesh models that can be created from both nadir and oblique aerial images. City authorities and national mapping agencies are interested in obtaining the 3D building models. Apart from the completeness of the models, the accuracy aspect is also important. Final accuracy of a building model depends on various factors (accuracy of the source data, complexity of the roof shapes, etc.). In this paper the methodology of inspection of dataset containing 3D models is presented. The proposed approach check all building in dataset with comparison to ALS point clouds testing both: accuracy and level of details. Using analysis of statistical parameters for normal heights for reference point cloud and tested planes and segmentation of point cloud provides the tool that can indicate which building and which roof plane in do not fulfill requirement of model accuracy and detail correctness. Proposed method was tested on two datasets: solid and mesh model.

scholarly journals QUALITY PREDICTION OF DENSE POINTS GENERATED BY STRUCTURE FROM MOTION FOR HIGH-QUALITY AND EFFICIENT AS-IS MODEL RECONSTRUCTION

2019 ◽  
Vol XLII-2/W13 ◽  
pp. 95-101
Author(s):  
R. Moritani ◽  
S. Kanai ◽  
H. Date ◽  
Y. Niina ◽  
R. Honma
Keyword(s):  
Structure From Motion ◽  
Point Clouds ◽  
Quality Prediction ◽  
Construction Site ◽  
Model Reconstruction ◽  
High Quality ◽  
Bridge Column ◽  
Dense Point ◽  
Selection Of

<p><strong>Abstract.</strong> In this paper, we introduce a method for predicting the quality of dense points and selecting low-quality regions on the points generated by the structure from motion (SfM) and multi-view stereo (MVS) pipeline to realize high-quality and efficient as-is model reconstruction, using only results from the former: sparse point clouds and camera poses. The method was shown to estimate the quality of the final dense points as the quality predictor on an approximated model obtained from SfM only, without requiring the time-consuming MVS process. Moreover, the predictors can be used for selection of low-quality regions on the approximated model to estimate the next-best optimum camera poses which could improve quality. Furthermore, the method was applied to the prediction of dense point quality generated from the image sets of a concrete bridge column and construction site, and the prediction was validated in a time much shorter than using MVS. Finally, we discussed the correlation between the predictors and the final dense point quality.</p>

AUTOMATIC CONTOURING USING BICUBIC FUNCTIONS

Geophysics ◽  
1972 ◽  
Vol 37 (4) ◽  
pp. 669-674 ◽  
Author(s):  
R. C. Hessing ◽  
Henry K. Lee ◽  
Alan Pierce ◽  
Eldon N. Powers
Keyword(s):  
Spatial Distribution ◽  
Cross Sections ◽  
Digital Computer ◽  
Smooth Surface ◽  
Contour Line ◽  
Contour Maps ◽  
Volume Calculations ◽  
Contour Lines ◽  
Data Points ◽  
Automatic Contouring

A method is described for using a digital computer to construct contour maps automatically. Contour lines produced by this method have correct relations to given discrete data points regardless of the spatial distribution of these points. The computer‐generated maps are comparable to those drawn manually. The region to be contoured is divided into quadrilaterals whose vertices include the data points. After supplying values at each of the remaining vertices by using a surface‐fitting technique, bicubic functions are constructed on each quadrilateral to form a smooth surface through the data points. Points on a contour line are obtained from these surfaces by solving the resulting cubic equations. The bicubic functions may be used for other calculations consistent with the contour maps, such as interpolation of equally spaced values, calculation of cross‐sections, and volume calculations.

A Study on Face Contour Line Extraction using Adaptive Skin Color

2017 ◽  
Vol 7 (3) ◽  
pp. 383-391
Author(s):  
Young-Jung Yu ◽  
Seong-Ho Park ◽  
Sang-Ho Moon ◽  
Yeon-Jun Choi
Keyword(s):  
Skin Color ◽  
Contour Line ◽  
Line Extraction ◽  
Face Contour

ROBUST PROFILE VERIFICATION SCHEME BASED ON EAR REFERENCE COORDINATE SYSTEM

2004 ◽  
Vol 18 (04) ◽  
pp. 685-700
Author(s):  
BYUNG-GYU KIM ◽  
SUNG-YUN JUNG ◽  
DONG-JO PARK
Keyword(s):  
A Priori ◽  
Ccd Camera ◽  
Human Head ◽  
Contour Line ◽  
Feature Points ◽  
Verification Scheme ◽  
Contour Lines ◽  
Morphological Filtering ◽  
Filling Method ◽  
The Given

In this paper, a novel profile verification scheme based on the ear, contour lines and feature points from head profile images is proposed. From the side image of a human head taken by a CCD camera, the contour line of the image is extracted by the simple filling method and morphological filtering. Based on the reference coordinate set by using ear images enrolled in the database a priori, the features of the contour line such as the tip of the nose, bottom of the nose, eye point and so on are extracted. The contour of the given image is divided into segments by utilizing the extracted feature points. The directional code of each segment is proposed and the length of the segment is computed for generating the feature vector. The verification of the given profile is performed by matching these feature vectors with those of the enrolled database. The experimental results show validity of the developed method for feature extraction and profile verification.

scholarly journals Visualizations of the Doblar Accumulation Basin Based on the UAV Survey

2019 ◽  
Vol 1 ◽  
pp. 1-7
Author(s):  
Klemen Kozmus Trajkovski ◽  
Gašper Štebe ◽  
Dušan Petrovič
Keyword(s):  
3D Model ◽  
Weather Conditions ◽  
Point Clouds ◽  
Water Levels ◽  
Contour Lines ◽  
Digital Elevation ◽  
Short Period ◽  
Dense Point ◽  
Aerial Vehicle ◽  
Elevation Model

<p><strong>Abstract.</strong> Our research is based on a large case study of Unmanned Aerial Vehicle (UAV) surveys, modelling and visualizations of the Doblar accumulation basin. The various approaches for UAV surveying of large, demanding terrain configurations, and the benefits of surveying products used as a basis for other interdisciplinary hydrological and environmental services were researched. The demanding mountainous terrain, the steep slopes and deep and narrow streams required detailed pre-planning of the survey, including the pre-survey terrain overview. The accumulation basin was emptied merely for a short period; thus, the survey was performed in unfavourable weather conditions, which included coldness, snowfall and wind. Point clouds were generated and georeferenced from the 4377 recorded photos. The dense point cloud contained approximately 222 million points in the medium setting and more than a billion in the high setting. A 3D model was built from the data. This became the basis for numerous further analyses and for the presentation using cartographic principles: a digital elevation model with a resolution of 10&amp;thinsp;cm, an orthophoto with a resolution of 10&amp;thinsp;cm, a 3D model draped with orthophoto, contour lines with a 1&amp;thinsp;m interval, topographic profiles, calculations of volumes at different water levels, a flythrough, augmented reality and a video simulation of the water level changes. The model can also serve as a basis for hydraulic and environmental analysis and simulations or used for analyses of the accumulation and deposition of river material compared with previous and future surveys.</p>

scholarly journals DualFace: Two-stage drawing guidance for freehand portrait sketching

2021 ◽  
Vol 8 (1) ◽  
pp. 63-77
Author(s):  
Zhengyu Huang ◽  
Yichen Peng ◽  
Tomohiro Hibino ◽  
Chunqi Zhao ◽  
Haoran Xie ◽  
...  
Keyword(s):  
User Study ◽  
High Quality ◽  
Contour Lines ◽  
Global Guidance ◽  
Face Contour ◽  
Artistic Training ◽  
Portrait Drawing ◽  
Two Stages ◽  
Global And Local ◽  
Different Levels

AbstractSpecial skills are required in portrait painting, such as imagining geometric structures and facial detail for final portrait designs. This makes it a difficult task for users, especially novices without prior artistic training, to draw freehand portraits with high-quality details. In this paper, we propose dualFace, a portrait drawing interface to assist users with different levels of drawing skills to complete recognizable and authentic face sketches. Inspired by traditional artist workflows for portrait drawing, dualFace gives two-stages of drawing assistance to provide global and local visual guidance. The former helps users draw contour lines for portraits (i.e., geometric structure), and the latter helps users draw details of facial parts, which conform to the user-drawn contour lines. In the global guidance stage, the user draws several contour lines, and dualFace then searches for several relevant images from an internal database and displays the suggested face contour lines on the background of the canvas. In the local guidance stage, we synthesize detailed portrait images with a deep generative model from user-drawn contour lines, and then use the synthesized results as detailed drawing guidance. We conducted a user study to verify the effectiveness of dualFace, which confirms that dualFace significantly helps users to produce a detailed portrait sketch.

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