Paper Info
Title
Designing a camera placement assistance system for human motion capture based on a guided genetic algorithm.
Abstract
In multi-camera motion capture systems, determining the optimal camera configuration (camera positions and orientations) is still an unresolved problem. At present, configurations are primarily guided by a human operator’s intuition, which requires expertise and experience, especially with complex, cluttered scenes. In this paper, we propose a solution to automate camera placement for motion capture applications in order to assist a human operator. Our solution is based on the use of a guided genetic algorithm to optimize camera network placement with an appropriate number of cameras. In order to improve the performance of the genetic algorithm (GA), two techniques are described. The first is a distribution and estimation technique, which reduces the search space and generates camera positions for the initial GA population. The second technique is an error metric, which is integrated at GA evaluation level as an optimization function to evaluate the quality of the camera placement in a camera network. Simulation experiments show that our approach is more efficient than other approaches in terms of computation time and quality of the final camera network.
Year
DOI
Venue
2018
10.1007/s10055-017-0310-7
Virtual Reality
Keywords
Field
DocType
Multi-camera-based motion capture systems, Optimal camera configurations, Genetic algorithm, Optimization
Population,Motion capture,Computer vision,Camera placement,Computer science,Simulation,Camera auto-calibration,Smart camera,Artificial intelligence,Genetic algorithm,Match moving,Computation
Journal
Volume
Issue
ISSN
22
1
1359-4338
Citations 
PageRank 
References 
1
0.35
13
Authors
6
Name
Order
Citations
PageRank
Azeddine Aissaoui110.35
abdelkrim ouafi2414.88
Philippe Pudlo3114.63
Christophe Gillet430.73
Zine-Eddine Baarir510.69
Abdelmalik Taleb-ahmed69622.55