Semantic 3D Point Cloud Analysis of Outdoor Scenes
Team
Jhonatan Contreras, Sven Sickert
Motivation

This ongoing research is a collaboration between the Computer Vision Group at the Friedrich Schiller University Jena and the DLR (German Aerospace Center) Institute for Data Science in Jena. For LiDAR (Light detection and ranging) pulsed beams of light are used to measure distances from a scanner to the surface of objects in a scene to produce 3D point clouds. It is unstructured data composed of a collection of non-uniformly distributed points in a continuous space. In some cases, images are captured simultaneously during LiDAR campaigns to enrich these points with color information. In semantic segmentation we aim to assign one label from a set of pre-defined classes to each point of such a point cloud. For instance, in an urban outdoor scene, the classes could be natural terrain, vegetation, buildings, and cars among other classes. As a result, we get a meaningful (semantic) representation of the input data. This task is an important step in the development of intelligent systems in areas such as autonomous driving, urban planning, as well as disaster prevention and mitigation. A complete semantic understanding of the environment is crucial for automatic decision making.

Publications
2020
Jhonatan Contreras, Sven Sickert, Joachim Denzler:
Region-based Edge Convolutions with Geometric Attributes for the Semantic Segmentation of Large-scale 3D Point Clouds.
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. 13 (1) : pp. 2598-2609. 2020.
[bibtex] [pdf] [web] [doi] [abstract]
2019
Jhonatan Contreras, Joachim Denzler:
Edge-Convolution Point Net For Semantic Segmentation Of Large-Scale Point Clouds.
IEEE International Geoscience and Remote Sensing Symposium (IGARSS). Pages 5236-5239. 2019.
[bibtex] [web] [doi] [abstract]
Jhonatan Contreras, Sven Sickert, Joachim Denzler:
Automatically Estimating Forestal Characteristics in 3D Point Clouds using Deep Learning.
iDiv Annual Conference. 2019. Poster
[bibtex] [web] [abstract]
2017
Sven Sickert, Joachim Denzler:
Semantic Segmentation of Outdoor Areas using 3D Moment Invariants and Contextual Cues.
DAGM German Conference on Pattern Recognition (DAGM-GCPR). Pages 165-176. 2017.
[bibtex] [pdf] [doi] [abstract]