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Kai Storjohann

dblp:82/6664 · DBLP profile ↗
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2ranked-venue papers
1as first author
0since 2021 · last 1990
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 2 · 1 first-authorSystems, architecture and hardware · 1 · 1 first-authorGraphics, computer vision, multimedia, augmented reality and games · 1

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
2 papers
Robot navigation and mapping · 54% Transfer learning and domain adaptation · 18% Autonomous driving · 18%

Topics — the 6 heaviest of 8, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Robotics › Robot navigation and mapping
mobile robot navigation
0.011990
Visual obstacle detection for automatically guided vehicles · ICRA 1990
Robotics › Robot navigation and mapping
obstacle detection
0.011990
Visual obstacle detection for automatically guided vehicles · ICRA 1990
Robotics › Autonomous driving
perception
0.011990
Visual obstacle detection for automatically guided vehicles · ICRA 1990
Robotics › Robot navigation and mapping › obstacle detection
stereo-based obstacle detection
0.011990
Visual obstacle detection for automatically guided vehicles · ICRA 1990
Computer vision › 3D vision
stereo vision
0.011990
Visual obstacle detection for automatically guided vehicles · ICRA 1990
Machine learning › Representation and self-supervised learning › representation learning › dimensionality reduction › manifold learning
topographic maps
0.011990
Adapting Computer Vision Systems to the Visual Environment: Topographic Mapping · ECCV 1990

Methods — techniques the papers use, named apart from their topics

topographic mapping · 0.0stereo image processing · 0.0inverse perspective mapping · 0.0
YearPublicationVenuePosition
1990 Adapting Computer Vision Systems to the Visual Environment: Topographic Mapping
Thomas Zielke, Kai Storjohann, Hanspeter A. Mallot, Werner von Seelen
ECCV2
1990 Visual obstacle detection for automatically guided vehicles
abstract
A stereo obstacle detection system has been developed for automatically guided vehicles that operate on flat (factory) floors. The system does not attempt to reconstruct the 3D environment visually but simply tries to detect obstacles on the floor in the vehicle's path. The approach to stereo image processing uses inverse perspective mappings to facilitate matching of the binocular field of vision against the expected 3D structure of the environment. Assuming a known relative camera model, a geometrical image transformation is computed which essentially compensates the stereo disparities for the image points of the floor. After the mapping operation the images are compared and local mismatches are interpreted as possible obstacle locations. The system has been successfully tested in a factory environment. The implementation runs on standard microprocessor hardware in real time.>
Kai Storjohann, Thomas Zielke, Hanspeter A. Mallot, Werner von Seelen
ICRA1