Gender recognition problem has not been extensively studied in situations where the face cannot be accurately detected and it also can be partially occluded. In this contribution, a comparison of several characterisation methods of the face is presented and they are evaluated in four different experiments that simulate the previous scenario. Two of the characterisation techniques are based on histograms, LBP and local contrast values, and the other one is a new kind of features, called Ranking Labels, that provide spatial information. Experiments have proved Ranking Labels description is the most reliable in inaccurate situations. © 2009 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Andreu, Y., García-Sevilla, P., & Mollineda, R. A. (2009). Dealing with inaccurate face detection for automatic gender recognition with partially occluded faces. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5856 LNCS, pp. 749–757). https://doi.org/10.1007/978-3-642-10268-4_88
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