%0 Conference Proceedings
%4 sid.inpe.br/sibgrapi/2015/06.18.19.06
%2 sid.inpe.br/sibgrapi/2015/06.18.19.06.04
%@doi 10.1109/SIBGRAPI.2015.26
%T Recognition of Static Gestures Applied to Brazilian Sign Language (Libras)
%D 2015
%A Bastos, Igor Leonardo Oliveira,
%A Angelo, Michele Fúlvia,
%A Loula, Angelo Conrado,
%@affiliation Federal University of Bahia - UFBA
%@affiliation State University of Feira de Santana - UEFS
%@affiliation State University of Feira de Santana - UEFS
%E Papa, João Paulo,
%E Sander, Pedro Vieira,
%E Marroquim, Ricardo Guerra,
%E Farrell, Ryan,
%B Conference on Graphics, Patterns and Images, 28 (SIBGRAPI)
%C Salvador, BA, Brazil
%8 26-29 Aug. 2015
%I IEEE Computer Society
%J Los Alamitos
%S Proceedings
%K Histogram of Oriented Gradients, Zernike Invariant Moments, Neural Networks, Gesture Recognition, Libras.
%X This paper aims at describing an approach developed for the recognition of gestures on digital images. In this way, two shape descriptors were used: the histogram of oriented gradients (HOG) and Zernike invariant moments (ZIM). A feature vector composed by the information acquired with both descriptors was used to train and test a two stage Neural Network, which is responsible for performing the recognition. In order to evaluate the approach in a practical context, a dataset containing 9600 images representing 40 different gestures (signs) from Brazilian Sign Language (Libras) was composed. This approach showed high recognition rates (hit rates), reaching a final average of 96.77%.
%@language en
%3 PID3766353.pdf