Sequential Updating of Projective and Affine Structure from Motion
International Journal of Computer Vision
Computer Vision and Image Understanding
Swarm intelligence
Multiple view geometry in computer visiond
Multiple view geometry in computer visiond
Navigation using Affine Structure from Motion
ECCV '94 Proceedings of the Third European Conference-Volume II on Computer Vision - Volume II
Reducing Local Optima in Single-Objective Problems by Multi-objectivization
EMO '01 Proceedings of the First International Conference on Evolutionary Multi-Criterion Optimization
Introduction to Evolutionary Computing
Introduction to Evolutionary Computing
Guiding single-objective optimization using multi-objective methods
EvoWorkshops'03 Proceedings of the 2003 international conference on Applications of evolutionary computing
A fast and elitist multiobjective genetic algorithm: NSGA-II
IEEE Transactions on Evolutionary Computation
Multiobjectivizing the HP model for protein structure prediction
EvoCOP'12 Proceedings of the 12th European conference on Evolutionary Computation in Combinatorial Optimization
Locality-based multiobjectivization for the HP model of protein structure prediction
Proceedings of the 14th annual conference on Genetic and evolutionary computation
An improved multiobjectivization strategy for HP model-based protein structure prediction
PPSN'12 Proceedings of the 12th international conference on Parallel Problem Solving from Nature - Volume Part II
Approximated algorithms for the minimum dilation triangulation problem
Journal of Heuristics
| Hi-index | 0.00 |
The triangulationis a process by which the 3D point position can be calculated from two images where that point is visible. This process requires the intersection of two known lines in the space. However, in the presence of noise this intersection does not occur, then it is necessary to estimate the best approximation. One option towards achieving this goal is the usage of evolutionary algorithms. In general, evolutionary algorithms are very robust optimization techniques, however in some cases, they could have some troubles finding the global optimum getting trapped in a local optimum. To overcome this situation some authors suggested removing the local optima in the search space by means of a single-objective problem to a multi-objective transformation. This process is called multi-objectivization. In this paper we successfully apply this multi-objectivizationto the triangulation problem.