Reconhecimento automático de expressões faciais baseado em características geométricas
In recent years we have seen great advances in Computer Vision research area that have made possible change the we interact with machines. To achieve an effective Intelligent Human-Computer Interface (IHC), in addition to recognize body movements or vocal commands, it is necessary the machine be abl...
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| Formato: | tesis de maestría |
| Estado: | Versión publicada |
| Fecha de publicación: | 2016 |
| País: | Brasil |
| Recursos: | Universidade Federal de Sergipe (UFS) |
| Repositorio: | Repositório Institucional da UFS |
| Idioma: | portugués |
| OAI Identifier: | oai:oai:ri.ufs.br:repo_01:riufs/3395 |
| Acesso em linha: | https://ri.ufs.br/handle/riufs/3395 |
| Access Level: | acceso abierto |
| Palavra-chave: | Computação Programas de computador Desenvolvimento de software Tecnologia da informação Reconhecimento de padrões Sistemas de reconhecimento de padrões Face Geometria facial CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO |
| Resumo: | In recent years we have seen great advances in Computer Vision research area that have made possible change the we interact with machines. To achieve an effective Intelligent Human-Computer Interface (IHC), in addition to recognize body movements or vocal commands, it is necessary the machine be able to understand human facial expressions. Although there are several publications that aims to recognize facial expressions, this task is not yet performed by a machine with the same efficiency as the human being. This work proposes two geometric-based feature selection approaches for facial expression recognition. The first, called Empirical Distances method obtained 77.66% of recognition rate. The second, called CFS Distances method, obtained 91.33% of recognition rate. The results obtained are compatible with the state of the art in this research area. |
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