Title
Automatic path generation for group dance performance using a genetic algorithm
Abstract
Designing dancers’ paths in choreography, or a floor pattern, is one of the most highly creative tasks of choreographers. Aiming to assist this task, this paper presents a novel system that automatically generates a number of floor patterns for multiple dancers given a choreographer’s high-level feature inputs. The proposed floor pattern model represents locomotor movements of dancers on stage. Through a dance literature survey, four major features, i.e., time, space, symmetry, and entropy, were selected as feature inputs and mathematically modeled. Our system uses a multi-objective genetic algorithm to achieve desired floor patterns given input features. It iterates from random floor patterns to the ones that satisfy users’ preferences while exploring the space of floor pattern with selection, mutation, crossover methods that are developed to fit the genotype of our system. User tests confirmed that our system generates a wide range of floor patterns according to user-specified input conditions. In addition, an actual dance piece was choreographed with the proposed method, which validated the usefulness of the proposed system. The proposed system is the first that automatically generates floor patterns for multiple dancers.
Year
DOI
Venue
2019
10.1007/s11042-018-6493-4
Multimedia Tools and Applications
Keywords
Field
DocType
Choreography, Dance floor pattern, Genetic algorithm
Dance,Crossover,Pattern recognition,Computer science,Path generation,Choreography,Artificial intelligence,Iterated function,Genetic algorithm
Journal
Volume
Issue
ISSN
78.0
6
1573-7721
Citations 
PageRank 
References 
0
0.34
15
Authors
2
Name
Order
Citations
PageRank
Jeong-seob Lee100.68
Sung-Hee Lee233424.19