@InProceedings{RezendeCastAlme:2016:ApBrSi,
               author = "Rezende, Tamires Martins and Castro, Cristiano Leite de and 
                         Almeida, S{\'{\i}}lvia Grasiella M.",
          affiliation = "{The Electrical Engineering Graduate Program - Federal University 
                         of Minas Gerais - Brazil} and {The Electrical Engineering Graduate 
                         Program - Federal University of Minas Gerais - Brazil} and 
                         Department of Industrial Automation - Federal Institute of Minas 
                         Gerais - Ouro Preto, Brazil",
                title = "An approach for Brazilian Sign Language (BSL) recognition based on 
                         facial expression and k-NN classifier",
            booktitle = "Proceedings...",
                 year = "2016",
               editor = "Aliaga, Daniel G. and Davis, Larry S. and Farias, Ricardo C. and 
                         Fernandes, Leandro A. F. and Gibson, Stuart J. and Giraldi, Gilson 
                         A. and Gois, Jo{\~a}o Paulo and Maciel, Anderson and Menotti, 
                         David and Miranda, Paulo A. V. and Musse, Soraia and Namikawa, 
                         Laercio and Pamplona, Mauricio and Papa, Jo{\~a}o Paulo and 
                         Santos, Jefersson dos and Schwartz, William Robson and Thomaz, 
                         Carlos E.",
         organization = "Conference on Graphics, Patterns and Images, 29. (SIBGRAPI)",
            publisher = "Sociedade Brasileira de Computa{\c{c}}{\~a}o",
              address = "Porto Alegre",
             keywords = "RGB-D sensor, Brazilian Sign Language, k-NN, Facial expression.",
             abstract = "The automatic recognition of facial expressions is a complex 
                         problem that requires the application of Computational 
                         Intelligence techniques such as pattern recognition. As shown in 
                         this work, this technique may be used to detect changes in 
                         physiognomy, thus making it possible to differentiate between 
                         signs in BSL (Brazilian Sign Language or LIBRAS in Portuguese). 
                         The methodology for automatic recognition in this study involved 
                         evaluating the facial expressions for 10 signs (to calm down, to 
                         accuse, to annihilate, to love, to gain weight, happiness, slim, 
                         lucky, surprise, and angry). Each sign was captured 10 times by an 
                         RGB-D sensor. The proposed recognition model was achieved through 
                         four steps: (i) detection and clipping of the region of interest 
                         (face), (ii) summarization of the video using the concept of 
                         maximized diversity, (iii) creation of the feature vector and (iv) 
                         sign classification via k-NN (k-Nearest Neighbors). An average 
                         accuracy of over 80\% was achieved, revealing the potential of 
                         the proposed model.",
  conference-location = "S{\~a}o Jos{\'e} dos Campos, SP, Brazil",
      conference-year = "4-7 Oct. 2016",
             language = "en",
                  ibi = "8JMKD3MGPAW/3MDH39S",
                  url = "http://urlib.net/ibi/8JMKD3MGPAW/3MDH39S",
           targetfile = "6.pdf",
        urlaccessdate = "2024, Apr. 27"
}