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Marco Pinter

dblp:136/0958 · DBLP profile ↗
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2ranked-venue papers
1as first author
0since 2021 · last 2014
0009-0004-2869-4777ORCID · corroborated

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

Graphics, computer vision, multimedia, augmented reality and games · 2 · 1 first-authorHuman-computer interaction and ubiquitous computing · 1 · 1 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
1 paper
Multi-agent systems · 100%
Human-computer interaction and pervasive computing
1 paper
Collaborative and social computing · 100%
Computer graphics and multimedia
1 paper
Computational photography and imaging · 100%

Topics — the 2 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Knowledge, reasoning and agents › Multi-agent systems › collective behavior
swarm behavior
0.212013
SwarmVision: autonomous aesthetic multi-camera interaction · ACM Multimedia 2013
Computational photography and imaging › multi-perspective imaging
multi-camera systems
0.012013
SwarmVision: autonomous aesthetic multi-camera interaction · ACM Multimedia 2013

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

negotiation · 0.5computer vision · 0.5autonomous control · 0.5
YearPublicationVenuePosition
2014 Generation of Engineering Research Directions Through Artistic Process
Marco Pinter, Angus G. Forbes, Danny Bazo, George Legrady
ArtsIT1
2013 SwarmVision: autonomous aesthetic multi-camera interaction
abstract
A platform of exploratory networked robotic cameras was created, utilizing an aesthetic approach to experimentation. Initiated by research in autonomous swarm robotic camera behavior, SwarmVision is an installation consisting of multiple Pan-Tilt-Zoom cameras on rails positioned above spectators in an exhibition space, where each camera behaves autonomously based on its own rules of computer vision and control. Each of the cameras is programmed to detect visual information of interest based on a different algorithm, and each negotiates with the other two, influencing what subject matter to study in a collective way. The emergent behaviors of the system illustrate an ongoing process of scene
George Legrady, Danny Bazo, Marco Pinter
ACM Multimedia3