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2nd International Workshop
Point Cloud Processing

When

Dec 4-5, 2019

Where

Stuttgart, Germany

About The Event

2nd International Workshop “Point Cloud Processing"

The 2nd International Workshop on Point Cloud Processing is a 1.5 day seminar co-organized by EuroSDR, the German Society for Photogrammetry, Remote Sensing and Geoinformationand (DGPF) and the Institute for Photogrammetry at the University of Stuttgart.

Topics | Focus

The quality of area covering 3D point clouds as captured by aerial and mobile mapping platforms still experiences a considerable boost due to the ongoing advancements in LiDAR technology and Multi-View-Stereo-Matching (MVS). In addition to further enhancement of the respective accuracy, density and reliability the semantic segmentation of these point clouds come more and more into focus. Also triggered by the astonishing improvements in the field of pattern recognition and machine learning, automatic interpretation of area covering point clouds including tasks like object detection and classification or object-dependent filtering and smoothing is moving rapidly to a mature state. In view of these developments, the meeting brings together experts from industry, academia and national mapping agencies to present and discuss the processing and evaluation of point clouds focusing on mapping purposes.

The program will provide a mix of invited speakers from industry, academia and governmental organizations as well as presentations selected on an abstract based review process.

Themes of the event include

  • acquisition & visualisation
  • data structures & management,
  • segmentation & classification,
  • object detection & reconstruction,
  • applications & use-cases from practice

 

Prospective presenters may send a 1000 word abstract to pcp2019@ifp.uni-stuttgart.de

Presentations| Call

Prospective presenters may send a 1000 word abstract to pcp2019@ifp.uni-stuttgart.de till October 7th.

Selection of presentations will be based on abstract review by the organizers. Workshop material will cover abstracts and presentation slides.

Venue | Accomodation

Venue

Guest house of Stuttgart University https://www.campus-guest.de/en/ located at the Campus Stuttgart-Vaihingen, in a 10 minutes distance with public transport to the city center of Stuttgart.

Accomodation

Rooms are available for 79 Euro per night directly at the venue https://www.campus-guest.de/en/. Alternatively an overview of hotels in Stuttgart can be found here.
A contingent of 50 rooms is reserved until Nov 4. Please use the code PCP2019 for your booking.

Event | Organizers

Norbert Haala

Norbert Haala

University of Stuttgart

Uwe Sörgel

Uwe Sörgel

University of Stuttgart

Michael Cramer

Michael Cramer

University of Stuttgart

Fabio Remondino

Fabio Remondino

FBK Trento, Italy

Event | program

Preliminary program

Wednesday, December 4th

11:30 – 13:00 / Opening + Presentations

Coffee Break

13:30-15:00  / Presentations

Coffee break

15:30-17:00  / Presentations

 

19:30 – 23:00 Uhr
Social dinner at Restaurant https://www.schlachthof-stuttgart.de/

 

Thursday, December 5th
9:00-10:30 / Presentations

Coffee break

11:00-12:30 / Presentations

Lunch

13:30 – 15:00 / Presentations and closing

 

Registration fee includes coffee breaks, social dinner at Wednesday, December 4th and lunch at Thursday, December 5th


Preliminary list of presentations

Sander Oude Elberink, Zhishuang Yang, Uni Twente
Using training samples retrieved from a topographic map for the classification of Airborne Laser Scanner data

Florian Gandor, Andre Streilein, Swisstopo
Point cloud processing at a national scale – advantages and challenges

Daniel Girardeau-Montaut CloudCompare
Point processing with CloudCompare

Boris Jutzi, KIT Karlsruhe
Self-Calibration for LiDAR-based Mobile Mapping Systems

Michael Kölle, Uni Stuttgart
Crowd-Based Active Learning on 3D Point Clouds

Dominik Laupheimer, Uni Stuttgart
Deriving Semantics from Textured Meshes

Loic Landrieu IGN, France
SuperPoint Graph state-of-the-art of deep learning methods for point cloud semantization, with a focus on scalable methods (including my article SuperPoint Graph).

N. Li, N. Pfeifer TU Wien
LiDAR point classification of power line facilities using the deep neutral network PointNet++

Gottfried Mandelburger,  TU Wien
Modern LIDAR Sensor Technologies – an Overview

Liangliang Nan, TU Delft
Accurate, detailed, and automatic reconstruction of real-world trees from point clouds

Ravi Peters TU Delft,
LoD2 building reconstruction from airborne point clouds

Florent Poux, University of Liège
Smart Point Cloud

Valentina Schmidt, Martin Kada, TU Berlin
Towards a Deep Learning Framework for 3D Building Reconstruction

Stefan Schmohl, Uni Stuttgart
3D CNN for the classification of point clouds

Martin Weinmann, KIT Karlruhe
Semantic Segmentation of Dense Point Clouds

Michael Weinmann, Uni Bonn
Let's be there - Sharing Immersive Live Telepresence Experiences based on Efficient Real-time 3D Reconstruction and Streaming

Konrad Wenzel, Tobias Hauck – nFrames
Dense Image Matching and LiDAR for large scale surface reconstruction

Lukas Winiwarter, Bernhard Höfle, Uni Heidelberg
Error budget of laser scanners: Applications in geomorphic surface change quantification

Yuxing Xie, Jiaojiao Tian, Xiao Xiang Zhu, Peter Reinartz, DLR Oberpfaffenhofen
Deep Learning-based Point Cloud Classification on Multiple Airborne LiDAR Datasets

Promo | video

Pricing | registration