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Ditemukan 15 dari pencarian Anda melalui kata kunci: subject="Point Cloud"
Hal. Awal Sebelumnya 1 2
cover
Semantic segmentation of point cloud data using raw laser scanner measurement…
Komentar Bagikan
Antero KukkoHarri KaartinenAimad El IssaouiRisto KaijaluotoJuha Hyyppa

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
Ketersediaan1
Tambahkan ke dalam keranjang
Unduh MARCSitasi
cover
Pavement distress detection using terrestrial laser scanning point clouds –…
Komentar Bagikan
Antero KukkoHarri KaartinenJuha HyyppZiyi FengAimad El IssaouiMatti LehtomakiMatias IngmanJoona SavelaHannu Hyyppa

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
Ketersediaan1
Tambahkan ke dalam keranjang
Unduh MARCSitasi
cover
Results of the ISPRS benchmark on indoor modelling
Komentar Bagikan
Kourosh KhoshelhamHa TranDebaditya AcharyaLucia Díaz VilariZhizhong KangSagi Dalyot

This paper reports the results of the ISPRS benchmark on indoor modelling. Reconstructed models submitted by 11 participating teams are evaluated on a dataset comprising 6 point clouds representing indoor environments of different complexity. The evaluation is based on measuring the completeness, correctness, and accuracy of the reconstructed wall elements through comparison with manually gener…

Edisi
Vol.2, December 2021
ISBN/ISSN
1872-8235
Deskripsi Fisik
13 hlm PDF, 4.462 KB
Judul Seri
ISPRS Open Journal of Photogrammetry and Remote Sensing
No. Panggil
621.3678
Ketersediaan1
Tambahkan ke dalam keranjang
Unduh MARCSitasi
cover
Efficient coarse registration method using translation- and rotation-invarian…
Komentar Bagikan
Eric HyyppaJesse MuhojokiXiaowei YuAntero KukkoHarri KaartinenJuha Hyypp

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
Ketersediaan1
Tambahkan ke dalam keranjang
Unduh MARCSitasi
cover
The Hessigheim 3D (H3D) benchmark on semantic segmentation of high-resolution…
Komentar Bagikan
Michael KolleDominik LaupheimerStefan SchmohlNorbert HaalaFranz RottensteinerJan Dirk WegnerHugo Ledoux

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
Ketersediaan1
Tambahkan ke dalam keranjang
Unduh MARCSitasi
Hal. Awal Sebelumnya 1 2
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