Genetic algorithms with sharing for multimodal function optimization
Proceedings of the Second International Conference on Genetic Algorithms on Genetic algorithms and their application
Polar IFS+Parisian Genetic Programming=Efficient IFS Inverse Problem Solving
Genetic Programming and Evolvable Machines
Dynamic flies: a new pattern recognition tool applied to stereo sequence processing
Pattern Recognition Letters
Comparing Viewpoint Evaluation Functions for Model-Based Inspectional Coverage
CRV '04 Proceedings of the 1st Canadian Conference on Computer and Robot Vision
3DPVT '04 Proceedings of the 3D Data Processing, Visualization, and Transmission, 2nd International Symposium
Automated photogrammetric network design using the parisian approach
EC'05 Proceedings of the 3rd European conference on Applications of Evolutionary Computing
Automatic sensor placement for model-based robot vision
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Parisian evolution with honeybees for three-dimensional reconstruction
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Fragmentation and Frontier Evolution for Genetic Algorithms Optimization in Music Transcription
IBERAMIA '08 Proceedings of the 11th Ibero-American conference on AI: Advances in Artificial Intelligence
Optimal camera placement for total coverage
ICRA'09 Proceedings of the 2009 IEEE international conference on Robotics and Automation
Can you see me now? sensor positioning for automated and persistent surveillance
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
A sensor placement approach for the monitoring of indoor scenes
EuroSSC'07 Proceedings of the 2nd European conference on Smart sensing and context
Discovering several robot behaviors through speciation
Evo'08 Proceedings of the 2008 conference on Applications of evolutionary computing
The cooperative royal road: avoiding hitchhiking
EA'07 Proceedings of the Evolution artificielle, 8th international conference on Artificial evolution
Optimal view path planning for visual SLAM
SCIA'11 Proceedings of the 17th Scandinavian conference on Image analysis
Active vision in robotic systems: A survey of recent developments
International Journal of Robotics Research
The honeybee search algorithm for three-dimensional reconstruction
EuroGP'06 Proceedings of the 2006 international conference on Applications of Evolutionary Computing
Covariance propagation and next best view planning for 3d reconstruction
ECCV'12 Proceedings of the 12th European conference on Computer Vision - Volume Part II
A behavior-based analysis of modal problems
Proceedings of the 15th annual conference companion on Genetic and evolutionary computation
Hi-index | 0.00 |
This paper presents a novel camera network design methodology based on the Parisian evolutionary computation approach. This methodology proposes to partition the original problem into a set of homogeneous elements, whose individual contribution to the problem solution can be evaluated separately. A population comprised of these homogeneous elements is evolved with the goal of creating a single solution by a process of aggregation. The goal of the Parisian evolutionary process is to locally build better individuals that jointly form better global solutions. The implementation of the proposed approach requires addressing aspects such as problem decomposition and representation, local and global fitness integration, as well as diversity preservation mechanisms. The benefit of applying the Parisian approach to our camera placement problem is a substantial reduction in computational effort expended in the evolutionary optimization process. Moreover, experimental results coincide with previous state of the art photogrammetric network design methodologies, while incurring in only a fraction of the computational cost.