Anzeige
Erschienen in:
2012 | OriginalPaper | Buchkapitel
Dissimilarity Representations Based on Multi-Block LBP for Face Detection
verfasst von : Yoanna Martínez-Díaz, Heydi Méndez-Vázquez, Yenisel Plasencia-Calaña, Edel B. García-Reyes
Erschienen in: Progress in Pattern Recognition, Image Analysis, Computer Vision, and Applications
Verlag: Springer Berlin Heidelberg
Aktivieren Sie unsere intelligente Suche, um passende Fachinhalte oder Patente zu finden.
Wählen Sie Textabschnitte aus um mit Künstlicher Intelligenz passenden Patente zu finden. powered by
Markieren Sie Textabschnitte, um KI-gestützt weitere passende Inhalte zu finden. powered by
Face representation is one of the open problems in face detection. The recently proposed Multi-Block Local Binary Patterns (MB-LBP) representation has shown good results for this purpose. Although dissimilarity representation has proved to be effective in a variety of pattern recognition problems, to the best of our knowledge, it has never been used for face detection. In this paper, we propose new dissimilarity representations based on MB-LBP features for this task. Different experiments conducted on a public database, showed that the proposed representations are more discriminative than the original MB-LBP representation when classifying faces. Using the dissimilarity representations, a good classification accuracy is achieved even when less training data is available.