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Session:

Workshop - Undergraduate Student Workshop

Title:

Interactive Evolutionary Strategies for Automatic Facial Composite Generation

 

 

Authors:

Merve Can Kus

 

 

Abstract:

The main aim of this project is to develop and analyze a program for the automatic face generation through interactive evolutionary strategies (IES). The user selects a number of images based on their similarity to a target image from a set of images presented to him via the interface. The generation of the facial images at each iteration are achieved by performing parent selection, recombination, mutation and survivor selection steps of evolutionary strategies (ES) and optimizing the T dimensional parameter vector of an active appearance model based on the selections of the user interactively. The main goal is to continue the iterations until the user is satisfied with at least one of the generated images. The program has been implemented and the preliminary tests show that IES gives successful results.

 

 

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