APPLICABILITY OF NEURAL NETWORKS FOR IMAGE CLASSIFICATION ON OBJECT DETECTION IN MOBILE MAPPING 3D POINT CLOUDS

Autor: Jürgen Döllner, Sören Discher, Rico Richter, Johannes Wolf

Publikováno v: The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLII-4-W15, Pp 111-115 (2019)

In this work, we present an approach that uses an established image recognition convolutional neural network for the semantic classification of two-dimensional objects found in mobile mapping 3D point cloud scans of road environments, namely manhole

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a637b9fb5b0ba637d4b234567ee4b7c5
https://www.int-arch-photogramm-remote-sens-spatial-inf-sci.net/XLII-4-W15/111/2019/isprs-archives-XLII-4-W15-111-2019.pdf

INTERACTION AND LOCOMOTION TECHNIQUES FOR THE EXPLORATION OF MASSIVE 3D POINT CLOUDS IN VR ENVIRONMENTS

Autor: Sören Discher, F. Thiel, Rico Richter, Jürgen Döllner

Publikováno v: The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Vol XLII-4, Pp 623-630 (2018)

Emerging virtual reality (VR) technology allows immersively exploring digital 3D content on standard consumer hardware. Using in-situ or remote sensing technology, such content can be automatically derived from real-world sites. External memory algor

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::27da4a0df92324c46311c12f14f2ecce
https://doi.org/10.5194/isprs-archives-xlii-4-623-2018

Concepts and techniques for web-based visualization and processing of massive 3D point clouds with semantics

Autor: Rico Richter, Sören Discher, Jürgen Döllner

3D point cloud technology facilitates the automated and highly detailed acquisition of real-world environments such as assets, sites, and countries. We present a web-based system for the interactive exploration and inspection of arbitrary large 3D po

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::13aacaf95b1780f5294257cb29743dae
https://publishup.uni-potsdam.de/frontdoor/index/index/docId/48920

Service-Oriented Processing and Analysis of Massive Point Clouds in Geoinformation Management

Autor: Rico Richter, Jürgen Döllner, Sören Discher, Matthias Trapp

Publikováno v: Lecture Notes in Geoinformation and Cartography ISBN: 9783319724331

Today, landscapes, cities, and infrastructure networks are commonly captured at regular intervals using LiDAR or image-based remote sensing technologies. The resulting point clouds, representing digital snapshots of the reality, are used for a growin

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::2aec75bae6a893aa89c73a0b54cfc31e
https://doi.org/10.1007/978-3-319-72434-8_2

Out-of-Core Visualization of Classified 3D Point Clouds

Autor: Jürgen Döllner, Rico Richter, Sören Discher

Publikováno v: Lecture Notes in Geoinformation and Cartography ISBN: 9783319121802

3D point clouds represent an essential category of geodata used in a variety of geoinformation applications and systems. We present a novel, interactive out-of-core rendering technique for massive 3D point clouds based on a layered, multi-resolution

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::bfe09d4deb69b37851cb08234566bdbe
https://doi.org/10.1007/978-3-319-12181-9_14