ON THE IMPORTANCE OF THE GRID SIZE FOR GENDER RECOGNITION USING FULL BODY STATIC IMAGES
Carlos Serra-Toro, V. Javier Traver, Raúl Montoliu, José Martínez Sotoca · 2011
In this paper we present an study on the importance of the grid configuration in gender recognition from whole body static images. By using a simple classifier (AdaBoost) and the well-known Histogram of Oriented Gradients features we test several grid configurations. Compared with previous approaches, which use more complicated classifiers or feature extractors, our approach outperforms them in the case of the frontal view recognition and almost equals them in the case of the mixed view (i.e. frontal and back views combined without distinction).