Ditapis dengan
Point cloud registration for LiDAR and photogrammetric data: A critical synth…
Three-dimensional (3D) point cloud registration is a fundamental step for many 3D modeling and mapping applications. Existing approaches are highly disparate in the data source, scene complexity, and application, therefore the current practices in various point cloud registration tasks are still ad-hoc processes. Recent advances in computer vision and deep learning have shown promising performa…
- Edisi
- Vol.8, April 2023
- ISBN/ISSN
- 1872-8235
- Deskripsi Fisik
- 13 hlm PDF, 8,236 KB
- Judul Seri
- ISPRS Open Journal of Photogrammetry and Remote Sensing
- No. Panggil
- 621.3678
Model-based constraints for trajectory determination of quad-copters: Design,…
This paper proposes a novel method to improve georeferencing of airborne laser scanning by improved trajectory estimation using Vehicle Dynamic Model. In Vehicle Dynamic Model (VDM), the relationship between the dynamics of the platform and control inputs is used as additional observations for sensor fusion. This relationship is available for most platforms and can be used without the need for …
- Edisi
- Vol.7, January 2023
- ISBN/ISSN
- 1872-8235
- Deskripsi Fisik
- 11 hlm PDF, 3.786 KB
- Judul Seri
- ISPRS Open Journal of Photogrammetry and Remote Sensing
- No. Panggil
- 621.3678
Semantic segmentation of bridge components and road infrastructure from mobil…
Emerging mobile LiDAR mapping systems exhibit great potential as an alternative for mapping urban environments. Such systems can acquire high-quality, dense point clouds that capture detailed information over an area of interest through efficient field surveys. However, automatically recognizing and semantically segmenting different components from the point clouds with efficiency and high accu…
- Edisi
- Vol.6, December 2022
- ISBN/ISSN
- 1872-8235
- Deskripsi Fisik
- 24 hlm PDF, 35.447 KB
- Judul Seri
- ISPRS Open Journal of Photogrammetry and Remote Sensing
- No. Panggil
- 621.3678
Observation distribution modelling and closed-from precision estimation of sc…
Geometric features such as cylinders and planes are important objects of interest in terrestrial laser scanner surveys of complex scenes. The quality of the objects modelled from the laser scanner data is a function of many variables and geometric network design plays a key role in maximizing precision. The expected precision can be predicted at the planning stage from simulations of the enviro…
- Edisi
- Vol.6, December 2022
- ISBN/ISSN
- 1872-8235
- Deskripsi Fisik
- 18 hlm PDF, 9.072 KB
- Judul Seri
- ISPRS Open Journal of Photogrammetry and Remote Sensing
- No. Panggil
- 621.3678
Comparison of neural networks and k-nearest neighbors methods in forest stand…
In the remote sensing of forests, point cloud data from airborne laser scanning contains high-value information for predicting the volume of growing stock and the size of trees. At the same time, laser scanning data allows a very high number of potential features that can be extracted from the point cloud data for predicting the forest variables. In some methods, the features are first extracte…
- Edisi
- Vol.4, April 2022
- ISBN/ISSN
- 1872-8235
- Deskripsi Fisik
- 17 hlm PDF, 13.215 KB
- Judul Seri
- ISPRS Open Journal of Photogrammetry and Remote Sensing
- No. Panggil
- 621.3678
Semantic segmentation of point cloud data using raw laser scanner measurement…
Deep learning methods based on convolutional neural networks have shown to give excellent results in semantic segmentation of images, but the inherent irregularity of point cloud data complicates their usage in semantically segmenting 3D laser scanning data. To overcome this problem, point cloud networks particularly specialized for the purpose have been implemented since 2017 but finding the m…
- Edisi
- Vol.3, January 2022
- ISBN/ISSN
- 1872-8235
- Deskripsi Fisik
- 16 hlm PDF, 8.371 KB
- Judul Seri
- ISPRS Open Journal of Photogrammetry and Remote Sensing
- No. Panggil
- 621.3678
Pavement distress detection using terrestrial laser scanning point clouds –…
In this paper, we compared five crack detection algorithms using terrestrial laser scanner (TLS) point clouds. The methods are developed based on common point cloud processing knowledge in along- and across-track profiles, surface fitting or local pointwise features, with or without machine learning. The crack area and volume were calculated from the crack points detected by the algorithms. The…
- Edisi
- Vol.3, January 2022
- ISBN/ISSN
- 1872-8235
- Deskripsi Fisik
- 13 hlm PDF, 4.179 KB
- Judul Seri
- ISPRS Open Journal of Photogrammetry and Remote Sensing
- No. Panggil
- 621.3678
Monitoring aseismic fault creep using persistent urban geodetic markers gener…
High resolution and high accuracy distributed detection of fault creep deformation remains challenging given limited observations and associated change detection strategies. A mobile laser scanning-based change detection method that is capable of measuring centimeter-level near-field ( m from fault) deformation is described. The methodology leverages the use of man-made features in the built …
- Edisi
- Vol.2, December 2021
- ISBN/ISSN
- 1872-8235
- Deskripsi Fisik
- 12 hlm PDF, 6.019 KB
- Judul Seri
- ISPRS Open Journal of Photogrammetry and Remote Sensing
- No. Panggil
- 621.3678
Efficient coarse registration method using translation- and rotation-invarian…
In this paper, we present a simple, efficient, and robust algorithm for 2D coarse registration of two point clouds. In the proposed algorithm, the locations of some distinct objects are detected from the point cloud data, and a rotation- and translation-invariant feature descriptor vector is computed for each of the detected objects based on the relative locations of the neighboring objects. Su…
- Edisi
- Vol.2, December 2021
- ISBN/ISSN
- 1872-8235
- Deskripsi Fisik
- 16 hlm PDF, 4.155 KB
- Judul Seri
- ISPRS Open Journal of Photogrammetry and Remote Sensing
- No. Panggil
- 621.3678
The Hessigheim 3D (H3D) benchmark on semantic segmentation of high-resolution…
Automated semantic segmentation and object detection are of great importance in geospatial data analysis. However, supervised machine learning systems such as convolutional neural networks require large corpora of annotated training data. Especially in the geospatial domain, such datasets are quite scarce. Within this paper, we aim to alleviate this issue by introducing a new annotated 3D datas…
- Edisi
- Vol.1, October 2021
- ISBN/ISSN
- 1872-8235
- Deskripsi Fisik
- 11 hlm PDF., 8,202 KB
- Judul Seri
- ISPRS Open Journal of Photogrammetry and Remote Sensing
- No. Panggil
- 621.3678
Batas Wilayah 
Ekologi 
Fotogrametri 
Geografi 
Geologi 
GIS 
Ilmu Tanah 
Kartografi 
Manajemen Bencana 
Oceanografi 
Penginderaan Jauh 
Peta