Evolutionary algorithms in theory and practice: evolution strategies, evolutionary programming, genetic algorithms
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Extraction of Parametric Human Model for Posture Recognition Using Genetic Algorithm
FG '00 Proceedings of the Fourth IEEE International Conference on Automatic Face and Gesture Recognition 2000
Hierarchical multi-sensor image registration using evolutionary computation
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Human motion reconstruction from monocular images using genetic algorithms: Research Articles
Computer Animation and Virtual Worlds - Special Issue: The Very Best Papers from CASA 2004
Feature-based image registration by means of the CHC evolutionary algorithm
Image and Vision Computing
Probability evolutionary algorithm based human body tracking
EuroGP'06 Proceedings of the 2006 international conference on Applications of Evolutionary Computing
An approach to multimodal biomedical image registration utilizing particle swarm optimization
IEEE Transactions on Evolutionary Computation
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The paper proposes a unified direct approach to a number of problems arising in image processing. In particular, the areas of image registration, and object or pattern recognition are addressed when the images of interest display significant geometric distortion due to some physical or geometrical conditions. The proposed method performs a direct multi-objective search in image response space for an optimal piece-wise affine transformation of the images using a hybrid evolutionary algorithm. In its most general form, the entire algorithm works in two relatively independent passes. First, the global search attempts to find the optimal solution for the principal affine transformation. During the second pass, the correction procedure seeks for the optimal piecewise approximation of the actual image transformation using the result of the first pass as the initial approximation.