Detalhes bibliográficos
| Ano de defesa: |
2023 |
| Autor(a) principal: |
Ferreira, Cristiane Bastos Rocha
 |
| Orientador(a): |
Soares, Fabrízzio Alphonsus Alves de Melo Nunes
|
| Banca de defesa: |
Soares, Fabrízzio Alphonsus Alves de Melo Nunes,
Pedrini, Helio,
Santos, Edimilson Batista dos,
Borges, Díbio Leandro,
Fernandes, Deborah Silva Alves |
| Tipo de documento: |
Tese
|
| Tipo de acesso: |
Acesso aberto |
| Idioma: |
por |
| Instituição de defesa: |
Universidade Federal de Goiás
|
| Programa de Pós-Graduação: |
Programa de Pós-graduação em Ciência da Computação (INF)
|
| Departamento: |
Instituto de Informática - INF (RMG)
|
| País: |
Brasil
|
| Palavras-chave em Português: |
|
| Palavras-chave em Inglês: |
|
| Área do conhecimento CNPq: |
|
| Link de acesso: |
http://repositorio.bc.ufg.br/tede/handle/tede/13181
|
Resumo: |
Gigapixel images, also known as gigaimages, can be formed by merging a sequence of individual images obtained from a scene scanning process. Such images can be understood as a mosaic construction based on a large number of high resolution digital images. A gigapixel image provides a powerful way to observe minimal details that are very far from the observer, allowing the development of research in many areas such as pedestrian detection, surveillance, security, and so forth. As this image category has a high volume of data captured in a sequential way, its generation is associated with many problems caused by the process of generating and analyzing them, thus, applying conventional algorithms designed for non-gigapixel images in a direct way can become unfeasible in this context. Thus, this work proposes a method for scanning, manipulating and analyzing multiresolution Gigapixel images for pedestrian and face identification applications using traditional algorithms. This approach is analyzed using both Gigapixel images with low and high density of people and faces, presenting promising results. |
