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István Kókai

dblp:01/3555 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2007
—ORCID · none

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

Graphics, 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.

Computer graphics and multimedia
1 paper
Geometric modeling and processing · 88% Visualization and visual analytics · 12%

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

TopicWeightPapersLastEvidence papers
Geometric modeling and processing
3d morphable model
0.112007
Navigating in a Shape Space of Registered Models · IEEE Trans. Vis. Comput. Graph. 2007
Geometric modeling and processing › shape analysis
shape space
0.112007
Navigating in a Shape Space of Registered Models · IEEE Trans. Vis. Comput. Graph. 2007
Geometric modeling and processing
product design
0.012007
Navigating in a Shape Space of Registered Models · IEEE Trans. Vis. Comput. Graph. 2007

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

shape space navigation · 0.1morphable model · 0.1
YearPublicationVenuePosition
2007 Navigating in a Shape Space of Registered Models
abstract
New product development involves people with different backgrounds. Designers, engineers, and consumers all have different criteria, and these criteria interact. Early concepts evolve in this kind of collaborative context, and there is a need for dynamic visualization of the interaction between design shape and other shape-related design criteria. In this paper, a Morphable Model is defined from simplified representations of suitably chosen real cars, providing a continuous shape space to navigate, manipulate, and visualize. Physical properties and consumer-provided scores for the real cars (such as 'weight' and 'sportiness') are estimated for new designs across the shape space. This coupling allows one to manipulate the shape directly while reviewing the impact on estimated criteria, or conversely, to manipulate the criterial values of the current design to produce a new shape with more desirable attributes.
Randall C. Smith, Richard R. Pawlicki, István Kókai, Jörg Finger, Thomas Vetter
IEEE Trans. Vis. Comput. Graph.3