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Ralf Gerber

dblp:78/5980 · DBLP profile ↗
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5ranked-venue papers
4as first author
0since 2021 · last 2008
—ORCID · none

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

Artificial intelligence and machine learning · 4 · 3 first-authorGraphics, computer vision, multimedia, augmented reality and games · 3 · 3 first-author

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
Knowledge representation and reasoning · 80% Vision and language · 20%
Computer graphics and multimedia
1 paper
Multimedia analysis and retrieval · 100%

Topics — the 3 heaviest of 4, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Knowledge, reasoning and agents › Knowledge representation and reasoning › qualitative reasoning
qualitative spatial reasoning
0.112008
Representation of occurrences for road vehicle traffic · Artif. Intell. 2008
Computer vision › Vision and language › image captioning › multi-image captioning
image stream captioning
0.011998
(Mis?-) Using DRT for Generation of Natural Language Text from Image Sequences · ECCV (2) 1998
Multimedia analysis and retrieval
video captioning
0.011998
(Mis?-) Using DRT for Generation of Natural Language Text from Image Sequences · ECCV (2) 1998

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

discourse representation theory · 0.0
YearPublicationVenuePosition
2008 Representation of occurrences for road vehicle traffic
Ralf Gerber, Hans-Hellmut Nagel
Artif. Intell.1
2008 Conceptual representations between video signals and natural language descriptions
Michael Arens, Ralf Gerber, Hans-Hellmut Nagel
Image Vis. Comput.2
2002 Deriving Textual Descriptions of Road Traffic Queues from Video Sequences
Ralf Gerber, Hans-Hellmut Nagel, Heiko Schreiber
ECAI1
1998 (Mis?-) Using DRT for Generation of Natural Language Text from Image Sequences
Ralf Gerber, Hans-Hellmut Nagel
ECCV (2)1
1996 Knowledge representation for the generation of quantified natural language descriptions of vehicle traffic in image sequences
abstract
Our image sequence interpretation process, which generates conceptual descriptions of the behaviour of vehicles in real-world traffic scenes, essentially treated only a single vehicle (the agent) so far. Simultaneous behaviours of other vehicles in the scene have been formulated only relative to the agent. The approach discussed in this contribution allows us to quantify occurrences and thus to generate more global conceptual descriptions of behaviour by using natural language quantifiers. The semantics of such quantified occurrences are represented by special logic structures. Natural language descriptions are derived from these internal knowledge representations.
Ralf Gerber, Hans-Hellmut Nagel
ICIP (2)1