%0 Conference Proceedings
%4 sid.inpe.br/sibgrapi/2016/08.16.02.19
%2 sid.inpe.br/sibgrapi/2016/08.16.02.19.34
%T HAGR-D: A Gesture Recognition System based on CIPBR Algorithm
%D 2016
%A Santos, Diego George da Silva,
%A Fernandes, Bruno José Torres,
%A Bezerra, Byron Leite Dantas,
%@affiliation Universidade de Pernambuco
%@affiliation Universidade de Pernambuco
%@affiliation Universidade de Pernambuco
%E Aliaga, Daniel G.,
%E Davis, Larry S.,
%E Farias, Ricardo C.,
%E Fernandes, Leandro A. F.,
%E Gibson, Stuart J.,
%E Giraldi, Gilson A.,
%E Gois, João Paulo,
%E Maciel, Anderson,
%E Menotti, David,
%E Miranda, Paulo A. V.,
%E Musse, Soraia,
%E Namikawa, Laercio,
%E Pamplona, Mauricio,
%E Papa, João Paulo,
%E Santos, Jefersson dos,
%E Schwartz, William Robson,
%E Thomaz, Carlos E.,
%B Conference on Graphics, Patterns and Images, 29 (SIBGRAPI)
%C São José dos Campos, SP, Brazil
%8 4-7 Oct. 2016
%I Sociedade Brasileira de Computação
%J Porto Alegre
%S Proceedings
%K CIPBR, HMM, DTW, Gesture Recognition.
%X Gesture recognition has been an area of great interest and study in recent years due to the evolution of technology and computers processing power, generating a higher degree in the Interaction Human Computer (IHC). These advances now allow communication between man and machine through hand gestures or entire body, especially in games, after the advent of Microsoft Kinect and other depth sensors. This paper proposes a dynamic gesture recognition system for user hand. The system is evaluated in two bases of dynamic hand gestures from the literature. The experiments show that the proposed model overcomes other algorithms presented in the literature in hand gesture recognition tasks, achieving a classification rate of 97.49\% in the MSRGesture3D dataset and 98.43\% in the RPPDI dynamic gesture dataset.
%@language en
%3 sibgrap.pdf