%0 Conference Proceedings
%4 sid.inpe.br/sibgrapi/2018/09.02.19.18
%2 sid.inpe.br/sibgrapi/2018/09.02.19.18.51
%@doi 10.1109/SIBGRAPI.2018.00039
%T Single-Shot Person Re-Identification Combining Similarity Metrics and Support Vectors
%D 2018
%A Sales, Anderson Luís Cavalcanti,
%A Vareto, Rafael Henrique,
%A Schwartz, William Robson,
%A Chavez, Guillermo Camara,
%@affiliation Universidade Federal de Ouro Preto
%@affiliation Smart Sense Laboratory, Department of Computer Science, Universidade Federal de Minas Gerais
%@affiliation Smart Sense Laboratory, Department of Computer Science, Universidade Federal de Minas Gerais
%@affiliation Universidade Federal de Ouro Preto
%E Ross, Arun,
%E Gastal, Eduardo S. L.,
%E Jorge, Joaquim A.,
%E Queiroz, Ricardo L. de,
%E Minetto, Rodrigo,
%E Sarkar, Sudeep,
%E Papa, João Paulo,
%E Oliveira, Manuel M.,
%E Arbeláez, Pablo,
%E Mery, Domingo,
%E Oliveira, Maria Cristina Ferreira de,
%E Spina, Thiago Vallin,
%E Mendes, Caroline Mazetto,
%E Costa, Henrique Sérgio Gutierrez,
%E Mejail, Marta Estela,
%E Geus, Klaus de,
%E Scheer, Sergio,
%B Conference on Graphics, Patterns and Images, 31 (SIBGRAPI)
%C Foz do Iguaçu, PR, Brazil
%8 29 Oct.-1 Nov. 2018
%I IEEE Computer Society
%J Los Alamitos
%S Proceedings
%K re-ID, Person re-identification, handcrafted, CUHK01, PRID450s, Support Vectors, Similarity Metrics, single-shot.
%X Person Re-Identification is all about determining a person's entire course as s/he walks around camera-equipped zones. More precisely, person Re-ID is the problem of matching human identities captured from non-overlapping surveillance cameras. In this work, we propose an approach that learns a new low-dimensional metric space in an attempt to cut down multi-camera matching errors. We represent the training and test samples by concatenating handcrafted features. Then, the method performs a two-step ranking using elementary distance metrics and followed by an ensemble of weighted binary classifiers. We validate our approach on CUHK01 and PRID450s datasets, providing only a sample per class for probe and only a sample for gallery (single-shot). According to the experiments, our method achieves CMC Rank-1 results up to 61.1 and 75.4, following leading literature protocols, for CUHK01 and PRID450s, respectively.
%@language en
%3 Paper ID 81.pdf