Publicação

Long-term person reidentification: challenges and outlook

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Detalhes bibliográficos
Resumo:Person reidentification, i.e., retrieving a person of interest across several non-overlapping cameras, is a task that is far from trivial. Despite its great commercial value and wide range of applications (e.g., surveillance, intelligent environments, forensics, service robotics, marketing), it remains unsolved, even when the individuals do not change clothes during the recognition period. This paper provides an outlook on long-term person reidentification, an emerging research topic regarding when consecutive acquisitions of an individual can be found apart for days or even months, making such a task even more challenging. A long-term reidentification system using face recognition is presented to emphasize current techniques’ limitations.
Autores principais:Manhães, Anderson
Outros Autores:Matos, Gabriel; Cardoso, Douglas O.; Pinto, Milena F.; Colares, Jeferson; Leitão, Paulo; Brandão, Diego; Haddad, Diego
Assunto:Long-term person ReID Deep learning Computer vision Multimodal retrieval
Ano:2022
País:Portugal
Tipo de documento:comunicação em conferência
Tipo de acesso:acesso restrito
Instituição associada:Universidade Politécnica de Bragança
Idioma:inglês
Origem:Biblioteca Digital da UPB
Descrição
Resumo:Person reidentification, i.e., retrieving a person of interest across several non-overlapping cameras, is a task that is far from trivial. Despite its great commercial value and wide range of applications (e.g., surveillance, intelligent environments, forensics, service robotics, marketing), it remains unsolved, even when the individuals do not change clothes during the recognition period. This paper provides an outlook on long-term person reidentification, an emerging research topic regarding when consecutive acquisitions of an individual can be found apart for days or even months, making such a task even more challenging. A long-term reidentification system using face recognition is presented to emphasize current techniques’ limitations.

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