Análise multirresolução de imagens gigapixel para detecção de faces e pedestres

Detalhes bibliográficos
Ano de defesa: 2023
Autor(a) principal: Ferreira, Cristiane Bastos Rocha lattes
Orientador(a): Soares, Fabrízzio Alphonsus Alves de Melo Nunes lattes
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.