Demo Data from VLDB 2026 / reviewers in the wild / expert
Martine Époque
dblp:63/2989
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2005
—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 |
Computer animation and physical simulation · 100% | |
| Human-computer interaction and pervasive computing
1 paper |
Games and playful interaction · 100% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Computer animation and physical simulation › motion synthesis
choreography generation |
0.1 | 1 | 2005 | The dancing genome project: generation of a human-computer choreography using a genetic algorithm · ACM Multimedia 2005 |
Games and playful interaction
interactive art |
0.0 | 1 | 2005 | The dancing genome project: generation of a human-computer choreography using a genetic algorithm · ACM Multimedia 2005 |
Methods — techniques the papers use, named apart from their topics
motion capture · 0.1genetic algorithm · 0.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2005 | The dancing genome project: generation of a human-computer choreography using a genetic algorithmabstractIn this paper, we present an interactive genetic algorithm for the generation of human-computer choreography, using motion capture technology. First, we introduce the four steps of the algorithm to (1) define a movement vocabulary, (2) initialize movement sequences, (3) generate mutants, and (4) select mutant sequences to create a choreography. Then, we show how this approach is implemented in real time to create interaction among dancers. Finally, we run simulations to assess the convergence rate of the algorithm, before generating a simple duet for actual and virtual dancers. François-Joseph Lapointe, Martine Époque |
ACM Multimedia | 2 |