CENSUS HISTOGRAMS: A SIMPLE FEATURE EXTRACTION and MATCHING APPROACH FOR FACE RECOGNITION
Nenhuma Miniatura disponível
Data
2011-12-01
Autores
Chiachia, Giovani [UNESP]
Marana, Aparecido Nilceu [UNESP]
Ruf, Tobias
Ernst, Andreas
Título da Revista
ISSN da Revista
Título de Volume
Editor
World Scientific Publ Co Pte Ltd
Resumo
Most face recognition approaches require a prior training where a given distribution of faces is assumed to further predict the identity of test faces. Such an approach may experience difficulty in identifying faces belonging to distributions different from the one provided during the training. A face recognition technique that performs well regardless of training is, therefore, interesting to consider as a basis of more sophisticated methods. In this work, the Census Transform is applied to describe the faces. Based on a scanning window which extracts local histograms of Census Features, we present a method that directly matches face samples. With this simple technique, 97.2% of the faces in the FERET fa/fb test were correctly recognized. Despite being an easy test set, we have found no other approaches in literature regarding straight comparisons of faces with such a performance. Also, a window for further improvement is presented. Among other techniques, we demonstrate how the use of SVMs over the Census Histogram representation can increase the recognition performance.
Descrição
Palavras-chave
Face recognition, census transform, local binary patterns, histogram matching, feature extraction
Como citar
International Journal of Pattern Recognition and Artificial Intelligence. Singapore: World Scientific Publ Co Pte Ltd, v. 25, n. 8, p. 1337-1348, 2011.